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"publ_id": "wiesinger_2025-baa", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "wiesinger_klemens-2023-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wildt-tci", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "withalm_brigitte-2022-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wolffhardt-2026-prj", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "yoo-chaeran-2025-pr", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "zeilinger_matthias-2020-baa", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=948", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" } ], "keywords": [ "sharp features", "intensity", "scanning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, 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"workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2026/balvan-rsf/", "__class": "Publication" }, { "id": "kloos-2026-icv", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Cross-Section Visualization of RIMFAX Subsurface Data for PRo3D", "date": "2026-06-25", "abstract": "This thesis presents an interactive visualization approach for integrating subsurface radar data acquired by the Radar Imager for Mars’ Subsurface Experiment (RIMFAX) into a three-dimensional terrain context. RIMFAX radargrams represent subsurface reflections recorded along the Perseverance rover traverse and are therefore two-dimensional data embedded in three-dimensional space. To improve their spatial interpretability, this work\ninvestigates cross-sections that open the terrain along a selected path and display the corresponding radargram on a curtain-shaped surface.\n\nThe developed prototype supports both interactively drawn paths and imported rover traverses. A central challenge is the consistent classification of the terrain for paths containing sharp turns, concave regions, loops, or selfintersections. Several local approaches were investigated, including tiled clipping planes and a nearest-point heuristic based on a frozen viewing direction. These methods produced inconsistent or visually unclear classifications for geometrically complex paths.\n\nThe final method reformulates the clipping problem as a two-dimensional point-in-polygon classification. The path is combined with an additional reference point to form a closed polygon, and terrain vertices are projected into a common two-dimensional coordinate system and classified as inside or outside this polygon. The classification is computed on the CPU and transferred to the GPU as a per-vertex attribute, where interpolation\nand fragment discarding produce the visible terrain cut. For fixed inputs, this approach provides stable and reproducible results and handles concave paths more consistently than the explored local methods.\n\nA continuous curtain is generated along the complete cross-section path by expanding its line segments into vertical quads. Normalized arc-length texture coordinates provide a continuous horizontal parameterization and allow the radargram to be mapped according to distance along the path.\n\nThe implementation is written in F# using the Aardvark Platform and processes the terrain through its Out-of-Core Point Cloud (OPC) patch hierarchy. It therefore uses technologies, data structures, and rendering mechanisms compatible with later integration into PRo3D. Performance was evaluated on a system equipped with an 11th Gen Intel Core i7-1165G7 processor, Intel Iris Xe Graphics, and 16 GB of RAM. For the evaluated terrain view, the classification of approximately 1.91 million vertices required approximately 1.21 seconds on average. After classification, navigation with clipping and curtain rendering\nenabled remained interactive at approximately 54 frames per second during continuous camera movement.\n\nThe results demonstrate that the method provides a practical foundation for embedding RIMFAX radargrams into their corresponding terrain context. Remaining limitations include spikes along the clipped terrain boundary, gaps or overlaps between the terrain and curtain, preprocessing requirements for the radargram imagery, and semantically ambiguous results for some self-intersecting paths.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "result image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1607, "image_height": 829, "name": "kloos-2026-icv-result image.png", "type": "image/png", "size": 2562049, "path": "Publication:kloos-2026-icv", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/kloos-2026-icv/kloos-2026-icv-result image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/kloos-2026-icv/kloos-2026-icv-result image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5616, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Lucia", "lastname": "Kloos", "searchname": "Lucia Kloos", "is_teacher": false, "name": "Lucia Kloos", "publications": [ "kloos-2026-icv" ], "publications_first": [ "kloos-2026-icv" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5616", "__class": "Author" } ], "date_end": "2026-06-25", "date_start": "2026-01-01", "matrikelnr": "12122563", "supervisor": [ { "id": 166, "drupal_id": 111, "orcid_id": "0000-0002-8569-4149", "website": "https://www.cg.tuwien.ac.at/staff/EduardGröller", "firstname": "Eduard", "lastname": "Gröller", "searchname": "Eduard Gröller", "is_teacher": true, "name": "Eduard Gröller", "publications": [ "a-2001-ah", "a-2001-ahr", "a-2001-Rec", "Acquisto-1995-DCR", "alacruzECR2004", "Alharbi_2021", "Alsallakh_2012_RCW", "amabili-2024-smg", "amabili-2025-lpb", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov_2013_AMA", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2017-cffet", "amirkhanov-2018-withteeth", "amirkhanov-2019-manylands", "amirkhanov2010AMA", "amirkhanov2020visual", "Antonini2020", "Artner-2004-Hig", "Artner-2005-Hig", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Bartroli-2002-Pro", "Bartroli-2003-Geo", "Bartroli-2003-Non", "beham-2014-cupid", "Berger_2011_UAE", "Berger-1998-Col", "Berger-2000-Col", "Bruckner_Stefan_2015_VAS", "Bruckner-2003-The", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "burns-2007-fea", "Carata_2011_IVE", "Castro-1998-TFS", "Cornel_Daniel_2015_VOC", "cornel-2022-wih", "coto-2005-MAC", "Csebfalvi-1999-Fast", "Csebfalvi-1999-MIP", "Csebfalvi-2000-Fas", "Csebfalvi-2000-GELR", "Csebfalvi-2000-Gra", "Csebfalvi-2000-IVRBM", "Csebfalvi-2001-Fas", "Csebfalvi-2001-Int", "Csebfalvi-2001-NPVR", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "dataset-stagbeetle", "Dhanoa_2021", "dhanoa-2022-apm", "dhanoa-2025-dsg", "Diehl_2015", "Diehl_2021", "diehl-2013-VTA", "Diehl-2017-Albero", "Edi_2019_10_01", "eg-tut2005-iv", "eichner-2022-music", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "fernandez-2022-ergoexplorer", "fischel-1995-vis", "Fischel-1995-VLS", "Fischel-1997-CSVVP", "Fischel-1998-Cas", "fmistelbauer-2014-adict", "fritz-2009-ava", "Froehler_Berhnard_2015_ESM", "fuchs_vhml", "fuchs-2008-del", "Fuhr-1999-Multi", "Fuhrmann-1998-Rea", "fuhrmann-1998-reaX", "Furmanova_2018", "furmanova_2020", "furmanova-2024-bvp", "gall-2025-marv", "Gall2021", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu-2010-CIE", "Gillmann2021", "Glaeser-1997-EVG", "Glaeser-1998-AFa", "Glaeser-1998-Eff", "Glaeser-1999-Fas", "glanznig-2009-LAMC", "Grimm-2003-CPU", "Grimm-2003-HYP", "grimm-2004-arefined", "GRIMM-2004-FDM", "GRIMM-2004-FDMX", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P3", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", "Groeller-1995-IED", "groeller-1995-inter", "groeller-1995-lok", "groeller-1995-mod", "groeller-1995-non", "Groeller-1995-SDC", "groeller-1995-vis", "groeller-1996-ACE", "groeller-1996-avn", "Groeller-1998-TunVis", "Groeller-1998-VAD", "Groeller-1998-VDS", "Groeller-1999-Dat", "Groeller-1999-Vis", "Groeller-2000-Vis", "Groeller-2001-IDV", "groeller-2002-anw", "Groeller-2002-Ins", "groeller-2002-med", "groeller-2002-wiss", "groeller-2003-fea", "groeller-2003-med", "groeller-2003-scie", "groeller-2003-vol", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-abs", "groeller-2005-dia", "groeller-2005-foc", "groeller-2005-imp", "groeller-2005-impo", "groeller-2005-proc", "groeller-2005-sma", "groeller-2005-smar", "groeller-2005-volg", "groeller-2006-cgf", "groeller-2006-civ", "groeller-2006-ivt", "groeller-2006-tvcg", "groeller-2007-csu", "groeller-2007-fci", "groeller-2007-mva", "groeller-2007-vis", "groeller-2007-visII", "groeller-2007-vws", "groeller-2008-att2", "groeller-2008-How", "groeller-2008-hsp", "groeller-2008-irs", "groeller-2008-kav2", "groeller-2008-kav3", "groeller-2008-kav4", "groeller-2008-lsy", "Groeller-2010-CVC", "groeller-2010-How", "Groeller-2010-IFI", "Groeller-2010-IVVI", "groeller-2010-PTT", "Groeller-2011-HSH", "Groeller-2017-AMOS", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "groeller-2022-iva", "groeller-2022-iva-1", "groeller-2022-ivd", "groeller-2023-ivd", "groeller-2023-siv", "groeller-2023-siv-1", "groeller-2023-siv-2", "groeller-2023-tfo", "groeller-2024-cui", "groeller-cvc-2009", "groeller-scv-2009", "groeller-svo-2009", "Groeller-thesis", "groeller-vks-2009", "Groller_2021-12-03", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "grossmann-2022-conceptSplatters", "Hadwiger-2003-MIP", "haidacher_2010_statTF", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-VAM", "Halladjian_2020", "Hauser-1999-SSI", "Hauser-2000-Tho", "Hauser-2000-Two", "Hauser-2000-TwoX", "Hauser-2002-SSI", "Hauser-2003-Acc", "Heim_2021", "heim-2024-accustripes", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2007-sem", "heinzl-2008-sam", "Herghelegiu-2012-BPV", "herzberger-2024-roh", "Hladuvka-2000-Cur", "Hladuvka-2000-Exp", "Hladuvka-2000-ExpX", "Hladuvka-2001-DDI", "Hladuvka-2001-Dir", "Hladuvka-2001-Exp", "Hladuvka-2001-Sal", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hladuvka-2002-Sma", "Jankovic-1994-PBM", "jankovic-1994-phy", "jankovic-1995-heter", "Kanitsar-2001-Aut", "Kanitsar-2001-Per", "Kanitsar-2001-Pos", "Kanitsar-2001-PVI", "kanitsar-2002-Chr", "Kanitsar-2002-CPR", "kanitsar-2002-CPRX", "Kanitsar-2003-ADV", "Kanitsar-2003-Adva", "Kanitsar-2003-CTa", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "karimov-2013-vivisection", "karimov-2016-SD", "kehrer-2013-SBC", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PMP", "klein-2016-WCL", "Knapp-2003-SAT", "knapp-2004-semi", "Knoll-2000-AJi", "Koechl-2003-Com", "Koenig-1998-NC", "Koenig-1998-Rea", "koenig-1999-AlV", "Koenig-1999-Mul", "Koenig-1999-MVA", "Koenig-2000-AlV", "Koenig-2000-AlVi", "Koenig-2000-ATFS", "Koenig-2001-Mas", "koeppel-2021", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "Korpitsch-2020-wscg", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "LaCruz-2004-NMF", "LaCruz2004", "lanzarotti-2025-viseps", "lee-2022-p", "Loeffelmann-1994-PSQ", "loeffelmann-1995-para", "Loeffelmann-1995-RTE", "loeffelmann-1996-CVA", "Loeffelmann-1996-DS3", "loeffelmann-1996-SVM", "Loeffelmann-1997-FV2", "Loeffelmann-1997-HSV", "Loeffelmann-1997-VPM", "Loeffelmann-1998-Enh", "Loeffelmann-1998-EVC", "Loeffelmann-1998-SMURF", "Loeffelmann-1998-VDS", "Loeffelmann-1998-Vis", "Loeffelmann-1998-Visu", "Loeffelmann-1999-SMU", "malik-2007-FP", "malik-2009-CVFA", "malik-2010-cvp", "manylands_award", "Matkovic-2002-Pro", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Meinhart-1998-Tun", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Milik-1997-GMMO", "Milik-1998-Geo", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2015-mc", "mindek-2017-dsn", "mindek-2017-marion", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Morar_2012_ISB", "Mroz-1998-Bri", "Mroz-1998-Sel", "Mroz-1998-SelX", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", 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"marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", 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"steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "kloos-2026-icv", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "SCHUETZ-2026-CURAST", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "eschner-2026-fpa", "Escribano_2017", "fitz-2026-isc", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "kloos-2026-icv", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "lehmann-2026-label", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "rupp-2026-zsa", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "telaar_sina-2026-baa", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "kloos-2026-icv-bachelor thesis.pdf", "type": "application/pdf", "size": 24765877, "path": "Publication:kloos-2026-icv", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/kloos-2026-icv/kloos-2026-icv-bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/kloos-2026-icv/kloos-2026-icv-bachelor thesis:thumb{{size}}.png" }, { "description": null, "filetitle": 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"exvisation", "Illustrare", "illvisation", "KASI", "ManyViews", "NeuroViewer", "ProcessIllVis", "ProKeyAnim", "PVG", "Scale-VS", "Scenario Pool", "Semantic Steering", "Sim-CT", "Smart-CT", "Smile Analytics", "ViMaL", "VISAR" ], "research_areas": [ "BioVis", "IllVis", "InfoVis", "MedVis", "NetVis", "Perception", "VisMat", "VR" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2015-image-coll", "2017-kouril-illcell", "2019-ic", "AA2020", "aigner-2025-vhv", "alacruzECR2004", "alacruzVisSym2004", "Alharbi_2021", "Alsallakh_2012_RCW", "alsallakh-2009-iva", "altendorfer-2008-vts", "amabili2021", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "amirkhanov2010AMA", "ammer-2008-lst", "An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-2026-fpa", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fitz-2026-isc", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", 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"https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2026/kloos-2026-icv/", "__class": "Publication" }, { "id": "slajcho_levente-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "CycleSafely - record depth images", "date": "2026-03-23", "abstract": "Tasks:\n- mount the devices by stativ interface (OAK-D, Insta 360 X2 ONE, Smartphone) on bicycle (helmet and handlebar) - possibly 3d print, ideally something low-threshold that everyone can easily construct\n- connect powerbank (<3mAh per hour, since 3A/5V) by cutting/connecting cables or finding a suitable adapter\n- oak-d: usb cable to smartphone, transfer point clouds to smartphone (SDK? python)\n- transfer photos from insta 360 to smartphone and de-fish eye it (get code from Aleks)\n- estimate depth from photo (for insta 360 and smartphone) - can maybe use the network from the camera (or camera directly)\n- client/server transfer (get code from Aleks) of point clouds to server (where pipeline of simon takes over the rest)\n\n\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 480, "image_height": 205, "name": "slajcho_levente-baa-image.png", "type": "image/png", "size": 173043, "path": "Publication:slajcho_levente-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/slajcho_levente-baa/slajcho_levente-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/slajcho_levente-baa/slajcho_levente-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5352, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Levente", "lastname": "Slajcho", "searchname": "Levente 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"Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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They cannot represent closed surfaces efficiently, and processing for geometrical applications like 3D printing is difficult. Therefore, we want to convert them to surface representations, most importantly, triangle meshes. This dissertation addresses the challenge of reconstructing accurate and robust 3D objects from imperfect point clouds. Traditional methods struggle with point cloud defects, motivating the exploration of data-driven approaches. However, deep learning on point clouds is difficult due to their unordered and unstructured nature. Further, subsampling is necessary to fit them into the fixed-size input of a neural network, which introduces randomness. In this thesis, we explore solutions for these challenges. We present three main contributions: Points2Surf, which combines local and global priors to generalize surface reconstruction across diverse object classes; PPSurf, which leverages point convolutions and attention to further improve reconstruction quality; and LidarScout, which enables real-time, out-of-core rendering of massive aerial LIDAR scans by focusing on efficient, local heightmap estimation. Our results demonstrate that balancing local detail with global context is key to achieving high-quality, generalizable reconstructions. We show that model design, data augmentation, and efficient representations are crucial for handling noise and missing data. The findings offer practical solutions for reconstructions from single objects to entire landscapes.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Reconstruction, 3D representations", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1440, "image_height": 501, "name": "erler_philipp-2017-phd-image.png", "type": "image/png", "size": 221151, "path": "Publication:erler_philipp-2017-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-image:thumb{{size}}.png" }, "sync_repositum_override": "abstract,date,keywords", "repositum_presentation_id": null, "authors": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", "firstname": "Philipp", "lastname": "Erler", "searchname": "Philipp Erler", "is_teacher": false, "name": "Philipp Erler", "publications": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout", "ilcik-2021-xmas" ], "publications_first": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout" ], "project_leader": [ "d4388" ], "publication_field": [ { "publ_id": "clemenz_2019_rosy_fields", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "clemenz_2019_rosy_fields", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "erler_2024_ppsurf", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2020-p2s", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2025-lidarscout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": 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"Angela Dai", "is_teacher": false, "name": "Angela Dai", "publications": [], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "erler_philipp-2017-phd", "field_id": "reviewer_1", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5558", "__class": "Author" } ], "reviewer_2": [ { "id": 1519, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Paolo", "lastname": "Cignoni", "searchname": "Paolo Cignoni", "is_teacher": false, "name": "Paolo Cignoni", "publications": [ "cardoso-2024-r-c", "WIMMER-2016-HARVEST4D" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "erler_philipp-2017-phd", "field_id": "reviewer_2", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1519", "__class": "Author" } ], "rigorosum": "2026-02-11", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", 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"field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", 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"reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], "keywords": [ "Surface Reconstruction", "Deep Learning", "Point Cloud" ], "weblinks": [], "files": [ { "description": "Reconstruction, 3D representations", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1440, "image_height": 501, "name": "erler_philipp-2017-phd-image.png", "type": "image/png", "size": 221151, "path": "Publication:erler_philipp-2017-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler_philipp-2017-phd-thesis.pdf", "type": "application/pdf", "size": 5503359, "path": "Publication:erler_philipp-2017-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2026/erler_philipp-2017-phd/erler_philipp-2017-phd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "ShapeAcquisition", "workgroup_id": "rend", "drupal_id": 4173, "drupal_path": "/research/projects/ShapeAcquisition", "name": "Real-Time Shape Acquisition with Sensor-Specific Precision", "name_de": null, "short_title": "ShapeAcquisition", "website": null, "status": "active", "short_abstract": "Acquiring shapes of physical objects in real time and with guaranteed precision to the noise model of the sensor devices.", "abstract": "

The core idea in this project is to capture the shape of physical objects in real time, with guaranteed precision, and to reconstruct the shape boundaries with minimal geometry. An example application is to let untrained users acquire shapes using emerging mobile sensing devices such as Google’s Project Tango. The user moves the sensor around the object, guided by immediate visual feedback on the input sampling quality. The output is a topologically clean mesh consisting of just the vertices required to represent its features to the desired approximation. The real-time reconstruction enables numerous geometry-processing applications to be taken online, such as shape retrieval/matching, harvesting real-world geometry into a cloud, perspective photo correction, interactive modeling, augmented reality, physics simulation, or fabrication.

\r\n", "start_date": "2015-12-01", "end_date": "2020-11-30", "leader_id": 193, "logo": { "name": "logo.jpg", "path": "project:ShapeAcquisition", "type": "image/jpeg", "size": 20004, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ShapeAcquisition/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P24600-N23", "comment": null } ], "research_areas": [ "Geometry" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "forsythe-2016-ccm", "grossmann-2016-baa", "gruber_horst-2019-baa", "koeppel-2016-baa", "novak_martin-2018-baa", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger-2016-sgp", "pointner_michael-2017-baa", "Radwan_2021_Occ", "Radwan-2017-Occ", "reinwald-2017-baa", "schaffarz_2018-pra", "schartmueller_2018_baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ShapeAcquisition", "__class": "Project" }, { "id": "d4388", "workgroup_id": "rend", "drupal_id": 4388, "drupal_path": "/research/projects/Images2Mesh-Web", "name": "Photogrammetry made easy", "name_de": "Photogrammetrie einfach gemacht", "short_title": "Images2Mesh Web", "website": null, "status": "active", "short_abstract": null, "abstract": "

Dieses Projekt richtet sich an alle Menschen, die gerne etwas in der echten Welt einscannen und anderen Menschen als 3D-Modell zeigen wollen. Beispielsweise könnte ein Artist unterwegs eine interessante Skulptur finden und diese in ein Spiel einbauen oder als Miniatur ausdrucken. Raumplaner könnten z.B. eine Kreuzung einscannen, nach ihren Plänen verändern und diese damit besser kommunizieren.

", "start_date": "2020-12-01", "end_date": "2024-03-31", "leader_id": 1395, "logo": { "name": "logo.png", "path": "project:d4388", "type": "image/png", "size": 1173196, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d4388/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Modeling" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "pichler_2022_fro", "steinschorn-2023-p2m" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Images2Mesh-Web", "__class": "Project" }, { "id": "Superhumans", "workgroup_id": "rend", "drupal_id": 4166, "drupal_path": "/research/projects/Superhumans", "name": "Superhumans - Walking Through Walls", "name_de": null, "short_title": "Superhumans", "website": null, "status": "active", "short_abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

\r\n", "abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" } ], "keywords": [ "slam", "registration", "mobile" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, 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"https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/", "__class": "Publication" }, { "id": "weydemann-2025-noo", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/221804", "title": "Non-uniform offsetting of surfaces", "date": "2025-11", "abstract": "Offset surfaces are fundamental in computer graphics applications, such as computer-aided design or tool-path generation. However, generating them while preserving geometric details and handling self-intersections remains challenging, particularly for surfaces with sharp features. This thesis presents a robust method for non-uniform offset surface generation, extending volumetric, feature-preserving uniform offset approaches to allow per-vertex control over offset distances. This enables greater flexibility in handling complex geometries and user-defined specifications.To achieve a smooth distribution of offsets across the input mesh, the method introduces a Radial Basis Function interpolation combined with Dijkstra-based distance propagation. The method supports the extraction of both inner and outer offset components through an octree data structure and a modified Dual Contouring algorithm adapted for non-uniform distances, ensuring accurate and manifold surface generation. This approach's adaptability and robustness are demonstrated across diverse input models with varying offset assignments. They showcase successful extraction of inner and outer components and the ability to capture localized asymmetries while preserving geometric integrity.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1211, "image_height": 494, "name": "weydemann-2025-noo-teaser.png", "type": "image/png", "size": 321957, "path": "Publication:weydemann-2025-noo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ { "id": 5531, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Tazzio Ludwig", "lastname": "Weydemann", "searchname": "Tazzio Ludwig Weydemann", "is_teacher": false, "name": "Tazzio Ludwig Weydemann", "publications": [ "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016" ], "publications_first": [ "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5531", "__class": "Author" } ], "ac_number": "AC17720179", "date_end": "2025-11-24", "date_start": "2016-08-11", "diploma_examina": "2025-11-24", "doi": "10.34726/hss.2025.40588", "matrikelnr": "00925369", "open_access": "yes", "pages": "92", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", 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"depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuericht-2026-GPUCDR", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "RAOULZADEH-2026-STROKES2DEFORM", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2026-shwizard", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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"field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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"supervisor", "ordernum": 1 }, { "publ_id": "tumpach_barbara-pra", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vasiljevic-gpc", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "wagentristl_stefan-2026-baa", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "wiesinger_2025-baa", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "wiesinger_klemens-2023-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wildt-tci", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "withalm_brigitte-2022-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wolffhardt-2026-prj", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "yoo-chaeran-2025-pr", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "zeilinger_matthias-2020-baa", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=948", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1137, "image_height": 667, "name": "macho_jonas-2024-baa-image.jpg", "type": "image/jpeg", "size": 201809, "path": "Publication:macho_jonas-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "macho_jonas-2024-baa-thesis.pdf", "type": "application/pdf", "size": 1938594, "path": "Publication:macho_jonas-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-thesis.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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In the case of autonomous driving, a\n\ncombination of modalities is used to complement other modalities weaknesses.\nWhile LIDAR sensors offer great depth and reflection information precision, the\noutput is a sparsely populated point cloud. 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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"WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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"Visualizing change detection on mobile", "date": "2025-08-12", "abstract": "Tasks:\n- Mit ToF Kamera und RGB Kamera (neueres Android Smartphone, Kinect, OAK-D Wide Pro) Tiefenbild und RGB Bild aufnehmen (haben jeweils leicht verschiedene Kameraparameter, das muss transformiert werden, sodass es sich überdeckt)\n- Change Detection (implementiert wer anderer) durchführen, die Punkte markiert: entweder infinitam.org auf Android portieren oder mittels Client/Server an den Server an der TU falls nicht möglich\n- Changes als markierte Pixel (Augmented Reality) über dem aktuellen RGB-Bild auf dem Smartphone anzeigen\n- Evaluierung: wie schnell kann die Registrierung, Change Detection und Visualisierung dargestellt werden und wie genau (ausgenommen Change detection) ist sie\n\n\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 489, "image_height": 254, 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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The resulting point cloud data sets are so massive in size that even basic tasks like viewing take hours to days of pre-processing in order to create level-of-detail structures that allow inspecting the data set in their entirety in real time. In this paper, we propose a method that is capable of instantly visualizing massive country-sized scans with hundreds of billions of points. Upon opening the data set, we first load a sparse subsample of points and initialize an overview of the entire point cloud, immediately followed by a surface reconstruction process to generate higher-quality, hole-free heightmaps. As users start navigating towards a region of interest, we continue to prioritize the heightmap construction process to the user's viewpoint. Once a user zooms in closely, we load the full-resolution point cloud data for that region and update the corresponding height map textures with the full-resolution data. As users navigate elsewhere, full-resolution point data that is no longer needed is unloaded, but the updated heightmap textures are retained as a form of medium level of detail. Overall, our method constitutes a form of direct out-of-core rendering for massive point cloud data sets (terabytes, compressed) that requires no preprocessing and no additional disk space. Source code, executable, pre-trained model, and dataset are available at: https://github.com/cg-tuwien/lidarscout", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2456, "image_height": 1411, "name": "erler-2025-lidarscout-teaser.jpg", "type": "image/jpeg", "size": 421958, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,articleno", "repositum_presentation_id": null, "authors": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], "keywords": [ "Point-based models", "Mesh models", "Neural networks", "Reconstruction", "Aerial LIDAR" ], "weblinks": [ { "href": "https://github.com/cg-tuwien/lidarscout", "caption": "Repository of Viewer Source", "description": null, "main_file": 1 }, { "href": "https://github.com/cg-tuwien/lidarscout_training", "caption": "Repository of Training Source", "description": null, "main_file": 1 }, { "href": "https://www.youtube.com/watch?v=q7Ap-FHZufY&list=PLD5wBo3-8n8LVGp6BDOFuPgGANdoYg_uk&index=8", "caption": "Presentation from HPG 2025", "description": null, "main_file": 1 }, { "href": "https://doi.org/10.48436/443tr-j4096", "caption": "TUW Research Data Repository", "description": "Datasets, models, more results", "main_file": 0 } ], "files": [ { "description": "Datasets for training and testing, containing chunk points and GT patches", "filetitle": "Datasets", 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"main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2456, "image_height": 1411, "name": "erler-2025-lidarscout-teaser.jpg", "type": "image/jpeg", "size": 421958, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser:thumb{{size}}.png" }, { "description": "A screen capture of the viewer", "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-video.mp4", "type": "video/mp4", "size": 122979998, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video:video.mp4" }, { "description": "LidarScout Executable for Windows", "filetitle": "Viewer", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-Viewer.zip", "type": "application/x-zip-compressed", "size": 2360647751, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-Viewer.zip", "thumb_image_sizes": [] } ], "projects_workgroups": [ { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"birsak-2014-agtb", "birsak-2017-dpe", "birsak-2017-dpe", "Birsak-Michael-2012", "birsak-thesis", "birsak-thesis", "Birsak2018-SA", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "bodzenta-2026-baa", "Bogner-2008-MTh", "boindl_2013", "BOKSANSKY-2019-RTS", "BORZA-2012-Stellarium", "brandmair-2024-bind", "brandmair-2024-rust", "brandmair-2025-rub", "Brandorff_06_PON", "Brandorff_06_SKIN", "brenner_simon-2013-ba", "brugger-2020-tdp", "brugger-2020-tsdpbr", "brugger-2020-tsdpbr", "brunner_lukas_2022_ssb", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "Calatrava_2013_GPGPUSOA", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-thesis", "CHARALAMBOS-2007-HLOD", "charpenay-2013-PR", "charpenay-2014-sgn", "Che-2025", "CHIU-2008-PEN", "clemenz_2019_rosy_fields", "CORNEL-2010-VIS", "CORNEL-2014-AFRS", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "csecsy-fcd", "darovskikh_leonid-2025-prj", "dataset", "dataset-cat", "dataset-chair", "dataset-dragon", "dataset-duck", "dataset-ferris-wheel", "dataset-penguin", "dataset-strauss", "dataset-tramway", "dataset-viennacity", "daubner-2007-HDR", "deak-a3", "deix-2008-rcp", "dellmour-2013-grs", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuericht-2026-GPUCDR", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "RAOULZADEH-2026-STROKES2DEFORM", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2026-shwizard", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/", "__class": "Publication" }, { "id": "wiesinger_2025-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Using a drone for automated 3D Scanning", "date": "2025-03-28", "abstract": "Drones have been widely adopted over the past decades, aiding in critical tasks such as\nsearch and rescue, inspection, and mapping. Autonomous drone scanning could further\nsupport such missions, but remains a significant challenge in indoor environments. This\nthesis explores the feasibility of using a consumer drone for such autonomous indoor 3D\nscanning. Our approach combines a DJI Spark drone, a lightweight Pico Flexx depth\nsensor, and a Raspberry Pi to capture depth data, which is streamed to an external\nserver for real-time processing. The system leverages ROS 2 and InfiniTAM for SLAM\nand map reconstruction, while navigation commands are issued via a smartphone using\nDJI’s Mobile SDK.\nAlthough the system successfully completed a limited autonomous scan, various con-\nstraints—including the drone’s payload capacity, limited sensor range, and hardware\ninstabilities—posed significant challenges. Despite these limitations, a modular software\narchitecture was developed that integrates sensing, mapping, and navigation. This\nframework provides a solid foundation for future work toward fully autonomous indoor\nscanning with more capable hardware. However, generating the next best view and\nfinding a feasible path toward it remain open challenges.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5296, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Klemens", "lastname": "Wiesinger", "searchname": "Klemens Wiesinger", "is_teacher": false, "name": "Klemens Wiesinger", "publications": [ "wiesinger_2025-baa", "wiesinger_klemens-2023-baa" ], "publications_first": [ "wiesinger_2025-baa", "wiesinger_klemens-2023-baa" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5296", "__class": "Author" } ], "date_end": "2025-03-28", "date_start": "2023-07-13", "matrikelnr": "11938253", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_Mistelbauer_2013_CSR", "bagar2010", "bernhard-2010-gph", "bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "birsak-2013-sta", "birsak-2014-agtb", "birsak-2017-dpe", "Bittner-2001-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brugger-2020-tdp", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "celarek-2025-d3g", "CHARALAMBOS-2007-HLOD", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "dataset-viennacity", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "erler_2024_ppsurf", "erler-2020-p2s", "erler-2025-lidarscout", "fink-2012-cg1", "fink-2013-cag", "freude_2020_rs", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "GRELAUD-2009-EPA", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2012_PSP", "Habel_LSN_2011", "Habel-2010-EIN", "hafner-2015-onff", "hecher-2014-MH", "HECHER-2017-HDY", "Honic_2021", "honic-2020-w78", "HU-2017-ETM", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2016-cescg", "ilcik-2016-cmssg", "JAHRMANN-2013-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ISTAR", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "Jimenez_SSS_2015", "Kathi-2018-VRB", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "klaffenboeck-2024-rva", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2011-CBCM", "KOCH-2021-GVS", "koenigsberger-2024-msu", "kovacs-2023-ttm", "KREUZER-2015-DPA", "kristmann-2026-vtc", "Kroesl_2020_11_09", "kroesl-2017-LiteMaker", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2020-XREye", "leimer_2017_rbpesc", "leimer-2016-rpe", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "MANTLER-2007-DMBBC", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "matt2011", "MATTAUSCH-2006-AVC", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "musialski-2015-souos", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger-2016-sgp", "OTEPKA-2020-PPC", "panfili-2021-myop", "pistellato-2023-elp", "preiner_2010_GIPC", "preiner_2012_AS", "Preiner_2019", "preiner2014clop", "PUEYO-2019-SCL", "PURGATHOFER-2006-IHB", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "reisinger-2023-iad", "ROEGNER-2015-IBR", "roth_vdi", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "santos-2017-dacge", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer2011c", "scherzer2011d", "SCHUETZ-2015-HQP", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "SSMW09", "stappen_SteFAS", "steiner_2016_isad", "STEINLECHNER-2019-APS", "STURN-2013-LGI", "STURN-2013-LSI", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "TR 193-02-2019-4", "TR 193-2-2019-4", "TR-186-2-02-04", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-12-01", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "wallner-2015-ModelingRoutinization", "WEBER-2015-PRA", "Wimmer-1996-ITB", "Wimmer-1997-ITT", "Wimmer-1998-Fas", "Wimmer-1998-SMO", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-CCL", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "Wimmer-2006", "WIMMER-2006-CES", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Wimmer-thesis", "wonka-2000-VisP", "wonka-2000-VisX", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "xmas-2023", "ymca", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "publications_first": [ "dataset-viennacity", "Wimmer-1996-ITB", "Wimmer-1997-ITT", "Wimmer-1998-Fas", "Wimmer-1998-SMO", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-CCL", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "Wimmer-2006", "WIMMER-2006-CES", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Wimmer-thesis" ], "project_leader": [ "3DSpatialization", "CROSSMOD", "d10070", "d10169", "d4307", "d4314", "d4342", "d4386", "d4559", "d4729", "d4958", "d4984", "d9259", "Desiree", "EVOCATION", "GameTools", "GAMEWORLD", "GPV", "Harvest4D", "INTRA-SPACE", "Landspotting", "Mofa", "OpenData", "PAMINA", "PathSpace", "Photo-Guide", "REPLICATE", "Scanopy", "SCI_BIM", "ShapeAcquisition", "TERAPOINTS", "Treelumination", "UrbanViz", "Wohnen 4.0" ], "publication_field": [ { "publ_id": "ADORJAN-2013-ASE", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Adorjan-2015", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "agyemang-2021-bsdfproxyppg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "aichner-2016-sadf", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "akan-vf", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Ams25", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "antes_sebastian-2026-msc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "antes-g", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "arikan-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ASCHL-2022-OTV", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "AUER-2010-PPT3D", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ausserer-2026-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "auzinger-2015-phd", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "auzinger-2015-phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "auzinger-dissertation", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "auzinger-dissertation", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "BAGAR-2010-LPB", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "balvan-g", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "BARSUKOV-2010-NEPC", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bauchinger-2007-mre", "field_id": 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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0 }, { "publ_id": "ZL_2011_IVIG", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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"https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", 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"title": "Observation and Tracking of Plant Health using Computer Vision", "date": "2025-02-19", "abstract": "- select neural network for classification of diseases, dryness of soil etc. with multispectral analysis, with open source, input should be image of plant bed (with several diverse plants), pipeline with segmentation (in same paper, or find segmentation paper)\n- optional: classify and segment plants\n- optional: growth analysis: blueten, wie schnell waechst die pflanze\n- search for data sets for training for generic plants (as many plants as possible), possibly combine several\n- evaluation with cheap IP RGB camera, and multispectral camera, e.g., RGB+IR or more\n- optional: evaluate soil dryness from images with dryness sensor\n \nresearch question: how well does such a system work with a commodity setup - for indoor and outdoor\nablation studies for indoor (more controlled environment) and outdoor, as well as RGB or RGB+IR++", "authors_et_al": false, "substitute": null, 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computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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"marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" } ], "keywords": [ "plants", "health monitoring", "computer vision" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 332, "image_height": 332, "name": "steinheber-2024-oto-image.png", "type": "image/png", "size": 212356, "path": "Publication:steinheber-2024-oto", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/", "__class": "Publication" }, { "id": "steinschorn-2025-par", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "SPSR Parameter determined by Neural Network", "date": "2025-01", "abstract": "In ’Parameter Optimization for Surface Reconstruction’ we tested different parameter optimization methods to find the most accurate and fast way to find optimal parameters for longer-running tasks that cannot be exhaustively tested. One strategy that we did not test is using machine learning to solve this problem. If it is possible to train a neural network to determine close-to-optimal parameters for a given task, then that would certainly be faster than all the other tested solutions. For this report, we generated training data for the problem of reconstructing meshes from point clouds using Screened Poisson Surface Reconstruction. We used ParamILS for this, and then tested two different networks to see if this is achievable. We describe our strategy for this, present our results, and discuss the encountered problems.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1757, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Florian", "lastname": "Steinschorn", "searchname": "Florian Steinschorn", "is_teacher": false, "name": "Florian Steinschorn", "publications": [ "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter" ], "publications_first": [ "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1757", "__class": "Author" } ], "date_end": "2025-01", "date_start": "2023-10", "matrikelnr": "1227109", "supervisor": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", "firstname": "Philipp", "lastname": "Erler", "searchname": "Philipp Erler", "is_teacher": false, "name": "Philipp Erler", "publications": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout", "ilcik-2021-xmas" ], "publications_first": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout" ], "project_leader": [ "d4388" ], "publication_field": [ { "publ_id": "clemenz_2019_rosy_fields", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "clemenz_2019_rosy_fields", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "erler_2024_ppsurf", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2020-p2s", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2025-lidarscout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hofer_kerstin-2023-sketch2model", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kapferer_2021_advancing", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pichler_2022_fro", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "riegler_2020_framework", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2023-p2m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-par", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-parameter", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1395", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], "keywords": [ "Deep Learning", "Surface Reconstruction", "Parameter Optimization", "Screened Poisson Surface Reconstruction" ], "weblinks": [ { "href": "https://github.com/thefloff/ppsurf_param_opt", "caption": "Repo", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-par-report.pdf", "type": "application/pdf", "size": 461075, "path": "Publication:steinschorn-2025-par", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/steinschorn-2025-par-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/steinschorn-2025-par-report:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "rend", "drupal_id": 1355, "name": "Rendering and Modeling", "website": "https://www.cg.tuwien.ac.at/group/Rendering-and-Modeling", "projects": [ "3DSpatialization", "CROSSMOD", "d10070", "d10169", "d10214", "d10381", "d4307", "d4314", "d4342", "d4386", "d4388", "d4559", "d4729", "d4958", "d4984", "d9259", "d9493", "d9691", "Desiree", "EU U-CREATE", "EU Virtual Showcases", "EVOCATION", "GameTools", "GAMEWORLD", "GPV", "Harvest4D", "INTRA-SPACE", "Landspotting", "MAKE-IT-FAB", "MARG", "Mofa", "OpenData", "PAMINA", "PathSpace", "Photo-Guide", "realreflect", "REPLICATE", "RESHADE", "Scanopy", "SCI_BIM", "ShapeAcquisition", "Skydome", "Superhumans", "TERAPOINTS", "Treelumination", "UrbanViz", "Visual Computing", "Wohnen 4.0", "WorldScale" ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Perception", "Rendering", "VR" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ADORJAN-2013-ASE", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "aichner-2016-sadf", "akan-vf", 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"bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "birsak-2014-agtb", "birsak-2017-dpe", "birsak-2017-dpe", "Birsak-Michael-2012", "birsak-thesis", "birsak-thesis", "Birsak2018-SA", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "bodzenta-2026-baa", "Bogner-2008-MTh", "boindl_2013", "BOKSANSKY-2019-RTS", "BORZA-2012-Stellarium", "brandmair-2024-bind", "brandmair-2024-rust", "brandmair-2025-rub", "Brandorff_06_PON", "Brandorff_06_SKIN", "brenner_simon-2013-ba", "brugger-2020-tdp", "brugger-2020-tsdpbr", "brugger-2020-tsdpbr", "brunner_lukas_2022_ssb", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "Calatrava_2013_GPGPUSOA", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-thesis", "CHARALAMBOS-2007-HLOD", "charpenay-2013-PR", "charpenay-2014-sgn", "Che-2025", "CHIU-2008-PEN", "clemenz_2019_rosy_fields", "CORNEL-2010-VIS", "CORNEL-2014-AFRS", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "csecsy-fcd", "darovskikh_leonid-2025-prj", "dataset", "dataset-cat", "dataset-chair", "dataset-dragon", "dataset-duck", "dataset-ferris-wheel", "dataset-penguin", "dataset-strauss", "dataset-tramway", "dataset-viennacity", "daubner-2007-HDR", "deak-a3", "deix-2008-rcp", "dellmour-2013-grs", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuericht-2026-GPUCDR", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", 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"hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "RAOULZADEH-2026-STROKES2DEFORM", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", 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"WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", 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"zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/", "__class": "Publication" }, { "id": "pointner_simon-2022-maa", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/225169", "title": "Cycle Safely", "date": "2025", "abstract": "This thesis presents a design and implementation of an end-to-end collision prediction and detection pipeline tailored to cyclists. The primary goal is to predict potential collisions between the cyclist (ego agent) and other road users, particularly motorised vehicles, which pose a higher risk due to higher momentum and speed. The proposed pipeline integrates conventional techniques for solving the sub-tasks of object detection, object tracking, and trajectory forecasting. Specifically, Super Fast and Accurate 3D Object Detection (SFA3D) is used for the detection, a Kalman filter-based multi-object tracker for temporal association of these detections, and a machine learning-based model (prediction conditioned on goals in visual multi-agent settings) is adapted and trained for the prediction of future trajectories. CARLA driving simulator facilitates the training and development of the prediction model by creating a synthetic dataset of cycling and the interaction with other road users. The system is evaluated on the synthetic dataset and also on the real-world KITTI dataset, and additional ablation studies examine the contribution of each pipeline stage. Experiments demonstrate that the proposed approach is capable of achieving reliable performance in object detection and tracking tasks. This confirms the feasibility of such a pipeline under limited sensing capabilities, such as LIDAR and GPS/IMU measurements. However, trajectory prediction remains a difficult and computationally expensive task, primarily due to the lack of documented and easily deployable open-source models. The implementation comes with a visualisation framework, built from the Rerun tool, for interactive inspection of the pipeline’s intermediate and final results.The contribution of this thesis can be summarised by the implementation of a framework for cyclist collision detection. It offers insights into how conventional and machine learning methods can be combined into a pipeline, and key limitations and points of future work for the creation of better trajectory prediction in adverse traffic contexts are outlined.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1796, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Simon", "lastname": "Pointner", "searchname": "Simon Pointner", "is_teacher": false, "name": "Simon Pointner", "publications": [ "pointner_simon-2020", "pointner_simon-2022-maa" ], "publications_first": [ "pointner_simon-2020", "pointner_simon-2022-maa" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1796", "__class": "Author" } ], "ac_number": "AC17754544", "co_supervisor": [ { "id": 948, "drupal_id": 185, "orcid_id": "0000-0002-2526-7700", "website": "https://www.cg.tuwien.ac.at/staff/StefanOhrhallinger", "firstname": "Stefan", "lastname": "Ohrhallinger", "searchname": "Stefan Ohrhallinger", "is_teacher": false, "name": "Stefan Ohrhallinger", "publications": [ "erler-2020-p2s", "leimer_2020-cag", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-2025-tsd", "ohrhallinger-stefan-2012-the", "parakkat-2024-ballmerge", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "SCHUETZ-2020-MPC", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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"filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pointner_simon-2022-maa-thesis.pdf", "type": "application/pdf", "size": 6379604, "path": "Publication:pointner_simon-2022-maa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pointner_simon-2022-maa/pointner_simon-2022-maa-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pointner_simon-2022-maa/pointner_simon-2022-maa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/marin-2024-sing/", "__class": "Publication" }, { "id": "hoffer-toth-com", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "CycleSafely on mobile", "date": "2024-08-12", "abstract": "SFA3D:\n\nZeitplan: Auf Mobile portiert bis Ende März / Anfang April.\n\nSAF3D ist mit Pytorch implementiert worden. Folgende Möglichkeiten gibt es um Pytorch Modelle auf Mobile/Android zu portieren:\n\n- Pytorch Mobile: https://pytorch.org/mobile/home/\n\n- Pytorch Flutter Plugins: https://pub.dev/packages/flutter_pytorch oder https://pub.dev/packages/pytorch_mobile\n\n- Deep Java Library: https://djl.ai/\n\n \n\n3D-Multi-Object-Tracker:\n\nZeitplan: Auf Mobile implementiert bis Ende April.\n\nDa 3DMOT ein non-ml Algorithmus ist, kann er in der dann gewählten Sprache implementiert werden.\n\n \n\nPrecog:\n\nZeitplan: Auf Mobile portiert bis Ende Mai.\n\nPrecog habe ich leider nicht zum Laufen bekommen, da ich nicht alle Daten gefunden habe bzw. nicht sicher war welche benötigt werden und wie sie konfiguriert werden sollen.\n\nPrecog verwendet Tensorflow. Dazu habe ich folgendes gefunden:\n\n- Tensorflow Lite: https://www.tensorflow.org/lite\n\n- Tflite Flutter: https://pub.dev/packages/tflite_flutter\n\n \n\nVergleich zwischen Server und Mobile:\n\nZeitplan: Server und Mobile werden Anfang Juni verglichen, wenn bis dahin alles nach Plan läuft.\n\n \n\nSchriftliche Arbeit:\n\nZeitplan: Mit dem Schreiben wird nach dem Vergleichen angefangen und dafür kann der Rest von Juni verwendet werden. Falls sich eines der Schritte herauszögert, dann kann ich die vorlesungsfreie Zeit im Sommer auch verwenden.\n\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 614, "image_height": 613, "name": "hoffer-toth-com-image.png", "type": "image/png", "size": 164978, "path": "Publication:hoffer-toth-com", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5353, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Matyas", "lastname": "Hoffer-Toth", "searchname": "Matyas Hoffer-Toth", "is_teacher": false, "name": "Matyas Hoffer-Toth", "publications": [ "hoffer-toth-com" ], "publications_first": [ "hoffer-toth-com" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5353", "__class": "Author" } ], "date_end": "2024-08-12", "date_start": "2024-03-11", "matrikelnr": "12122086", "supervisor": [ { "id": 948, "drupal_id": 185, "orcid_id": "0000-0002-2526-7700", "website": "https://www.cg.tuwien.ac.at/staff/StefanOhrhallinger", "firstname": "Stefan", "lastname": "Ohrhallinger", "searchname": "Stefan Ohrhallinger", "is_teacher": false, "name": "Stefan Ohrhallinger", "publications": [ "erler-2020-p2s", "leimer_2020-cag", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-2025-tsd", "ohrhallinger-stefan-2012-the", "parakkat-2024-ballmerge", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "SCHUETZ-2020-MPC", "ulschmid-2026-naadf" ], "publications_first": [ "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-2025-tsd", "ohrhallinger-stefan-2012-the" ], "project_leader": [ "d10381", 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}, { "publ_id": "rait_alexius-2021-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "reiher_joerg-2023-pra", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "reiher-joerg-2024-daa", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "reinwald-2017-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "resch_martin-2026-baa", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "rozanics-lsf", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "rubik_michael-2022-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "schaffarz_2018-pra", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "schartmueller_2018_baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "schefcik_juergen_2015_baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "schmid_andreas_2013-prj", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "schoerkhuber_dominik-2016-baa", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": 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"supervisor", "ordernum": 1 }, { "publ_id": "tumpach_barbara-pra", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vasiljevic-gpc", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "wagentristl_stefan-2026-baa", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "wiesinger_2025-baa", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "wiesinger_klemens-2023-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wildt-tci", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "withalm_brigitte-2022-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wolffhardt-2026-prj", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "yoo-chaeran-2025-pr", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "zeilinger_matthias-2020-baa", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=948", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" } ], "keywords": [ "bicycle", "mobile", "scanning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 614, "image_height": 613, "name": "hoffer-toth-com-image.png", "type": "image/png", "size": 164978, "path": "Publication:hoffer-toth-com", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "hoffer-toth-com-thesis.pdf", "type": "application/pdf", "size": 6093633, "path": "Publication:hoffer-toth-com", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/hoffer-toth-com-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/hoffer-toth-com/", "__class": "Publication" }, { "id": "ohrhallinger_stefan-2024-inv", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Sampling and reconstructing point clouds", "date": "2024-05-28", "abstract": "Curve and surface reconstruction from unstructured points represent a fundamental problem in computer graphics and computer vision, with many applications. The quest for better solutions for this ill-posed problem is riddled with various kinds of artifacts such as noise, outliers, and missing data.\n\nMoreover, the reconstruction problem usually implies further input requirements: how many samples do we need for a successful reconstruction, what properties should these samples satisfy and how can we obtain such sets. And once we obtain these point samples, how can we extract connectivity that best approximates the initial surface they have been sampled from?\n\nWe will discuss about various sampling strategies, corresponding reconstruction methods, with multiple applications in automating sketch coloring, adaptive meshing for faster simulations, and cultural heritage.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1310, "image_height": 596, "name": "ohrhallinger_stefan-2024-inv-image.png", "type": "image/png", "size": 762834, "path": "Publication:ohrhallinger_stefan-2024-inv", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/ohrhallinger_stefan-2024-inv/ohrhallinger_stefan-2024-inv-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/ohrhallinger_stefan-2024-inv/ohrhallinger_stefan-2024-inv-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 948, "drupal_id": 185, "orcid_id": "0000-0002-2526-7700", "website": "https://www.cg.tuwien.ac.at/staff/StefanOhrhallinger", "firstname": "Stefan", "lastname": "Ohrhallinger", "searchname": "Stefan Ohrhallinger", "is_teacher": false, "name": "Stefan Ohrhallinger", "publications": [ "erler-2020-p2s", "leimer_2020-cag", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-2025-tsd", "ohrhallinger-stefan-2012-the", "parakkat-2024-ballmerge", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "SCHUETZ-2020-MPC", "ulschmid-2026-naadf" ], "publications_first": [ "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-2025-tsd", "ohrhallinger-stefan-2012-the" ], "project_leader": [ "d10381", "Superhumans", "WorldScale" ], "publication_field": [ { "publ_id": "antes_sebastian-2026-msc", "field_id": "co_supervisor", "ordernum": 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"

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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In this paper, we analyze an alternative to the often-used k-nearest neighborhood (kNN) graph - the Spheres of Influence Graph (SIG). We show that the edges that are neighboring each vertex are spatially bounded, which allows for fast computation of SIG. Our approach shows a better encoding of the ground truth connectivity compared to the kNN for a wide range of k, and additionally, it is parameter-free. 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Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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], "projects_workgroups": [ { "id": "Superhumans", "workgroup_id": "rend", "drupal_id": 4166, "drupal_path": "/research/projects/Superhumans", "name": "Superhumans - Walking Through Walls", "name_de": null, "short_title": "Superhumans", "website": null, "status": "active", "short_abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

\r\n", "abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

\r\n", "start_date": "2019-09-01", "end_date": "2023-08-31", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:Superhumans", "type": "image/jpeg", "size": 96578, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Superhumans/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P32418-N31", "comment": "332.780,70 €" } ], "research_areas": [ "Geometry", "VR" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "leimer_2020-cag", "marin-2024-pcp", "parakkat-2024-ballmerge", "rait_alexius-2021-baa", "SCHUETZ-2020-MPC", "schuetz-2020-PPC" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Superhumans", "__class": "Project" }, { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/marin-2024-pcp/", "__class": "Publication" }, { "id": "erler_2024_ppsurf", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/192690", "title": "PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction", "date": "2024-01-12", "abstract": "Abstract 3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage and engineering. Current approaches either try to optimize a non-data-driven surface representation to fit the points, or learn a data-driven prior over the distribution of commonly occurring surfaces and how they correlate with potentially noisy point clouds. Data-driven methods enable robust handling of noise and typically either focus on a global or a local prior, which trade-off between robustness to noise on the global end and surface detail preservation on the local end. We propose PPSurf as a method that combines a global prior based on point convolutions and a local prior based on processing local point cloud patches. We show that this approach is robust to noise while recovering surface details more accurately than the current state-of-the-art. Our source code, pre-trained model and dataset are available at https://github.com/cg-tuwien/ppsurf.", "authors_et_al": false, "substitute": null, "main_image": { "description": "PPSurf teaser with comparison", "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2288, "image_height": 740, "name": "erler_2024_ppsurf-teaser.png", "type": "image/png", "size": 1734284, "path": "Publication:erler_2024_ppsurf", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/erler_2024_ppsurf/erler_2024_ppsurf-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/erler_2024_ppsurf/erler_2024_ppsurf-teaser:thumb{{size}}.png" }, "sync_repositum_override": "doi,number,volume", "repositum_presentation_id": null, "authors": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", "firstname": "Philipp", "lastname": "Erler", "searchname": "Philipp Erler", "is_teacher": false, "name": "Philipp Erler", "publications": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout", "ilcik-2021-xmas" ], "publications_first": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout" ], "project_leader": [ "d4388" ], "publication_field": [ { "publ_id": "clemenz_2019_rosy_fields", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "clemenz_2019_rosy_fields", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "erler_2024_ppsurf", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2020-p2s", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2025-lidarscout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hofer_kerstin-2023-sketch2model", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kapferer_2021_advancing", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pichler_2022_fro", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "riegler_2020_framework", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2023-p2m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-par", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-parameter", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1395", "__class": "Author" }, { "id": 5317, "drupal_id": null, "orcid_id": "0000-0003-1096-2871", "website": null, "firstname": "Lizeth", "lastname": "Fuentes-Perez", "searchname": "Lizeth Fuentes-Perez", "is_teacher": false, "name": "Lizeth Fuentes-Perez", "publications": [ "erler_2024_ppsurf" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5317", "__class": "Author" }, { "id": 1919, "drupal_id": null, "orcid_id": "0000-0002-7568-2849", "website": "https://cvl.tuwien.ac.at/staff/pedro-hermosilla-casajus/", "firstname": "Pedro", "lastname": "Hermosilla-Casajus", "searchname": "Pedro Hermosilla-Casajus", "is_teacher": false, "name": "Pedro Hermosilla-Casajus", "publications": [ "celarek-2022-gmcn", "erler_2024_ppsurf", "kovacs-2024-smt" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "staats-2024-atr", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1919", "__class": "Author" }, { "id": 627, "drupal_id": 271, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/PaulGuerrero", "firstname": "Paul", "lastname": "Guerrero", "searchname": "Paul Guerrero", "is_teacher": false, "name": "Paul Guerrero", "publications": [ "erler_2024_ppsurf", "erler-2020-p2s", "G_P_06_RFS", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY" ], "publications_first": [ "G_P_06_RFS", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp" ], "project_leader": [], "publication_field": [ { "publ_id": "Fuerst-2009-dfr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Guerrero-2014-GRF", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "guerrero-2015-lsp", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "MeierStauffer-2013-iihf", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "MuehlbacherArbesser-2009-LMDLightcuts", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=627", "__class": "Author" }, { "id": 1184, "drupal_id": null, "orcid_id": null, "website": "http://www.ifi.uzh.ch/vmml/people/current-staff/pajarola.html", "firstname": "Renato", "lastname": "Pajarola", "searchname": "Renato Pajarola", "is_teacher": false, "name": "Renato Pajarola", "publications": [ "Diehl_2021", "erler_2024_ppsurf", "MATTAUSCH-2015-CHCRT", "preiner2014clop" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1184", "__class": "Author" }, { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_Mistelbauer_2013_CSR", "bagar2010", 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"koenigsberger-2024-msu", "kovacs-2023-ttm", "KREUZER-2015-DPA", "kristmann-2026-vtc", "Kroesl_2020_11_09", "kroesl-2017-LiteMaker", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2020-XREye", "leimer_2017_rbpesc", "leimer-2016-rpe", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "MANTLER-2007-DMBBC", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "matt2011", "MATTAUSCH-2006-AVC", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "musialski-2015-souos", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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"fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], "keywords": [ "modeling", "surface reconstruction" ], "weblinks": [ { "href": "https://huggingface.co/spaces/perler/ppsurf", "caption": "Live System", "description": null, "main_file": 1 }, { "href": "https://github.com/cg-tuwien/ppsurf", "caption": "Repo (Github)", "description": null, "main_file": 1 }, { "href": "https://onlinelibrary.wiley.com/doi/10.1111/cgf.15000", "caption": "Official Publication (Wiley Computer Graphics Forum)", "description": null, "main_file": 0 }, { "href": "https://arxiv.org/abs/2401.08518", "caption": "Preprint (ArXiv)", "description": null, "main_file": 0 }, { "href": "https://www.replicabilitystamp.org/#https-github-com-cg-tuwien-ppsurf", "caption": "Graphics Replicability Stamp Initiative", "description": null, "main_file": 0 } ], "files": [ { "description": "Paper Reproduction Code and Models\nNote: use the repo instead of this 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"filetitle": "trainset", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler_2024_ppsurf-trainset.zip", "type": "application/x-zip-compressed", "size": 2513802131, "path": "Publication:erler_2024_ppsurf", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/erler_2024_ppsurf/erler_2024_ppsurf-trainset.zip", "thumb_image_sizes": [] } ], "projects_workgroups": [ { "id": "rend", "drupal_id": 1355, "name": "Rendering and Modeling", "website": "https://www.cg.tuwien.ac.at/group/Rendering-and-Modeling", "projects": [ "3DSpatialization", "CROSSMOD", "d10070", "d10169", "d10214", "d10381", "d4307", "d4314", "d4342", "d4386", "d4388", "d4559", "d4729", "d4958", "d4984", "d9259", "d9493", "d9691", "Desiree", "EU U-CREATE", "EU Virtual Showcases", "EVOCATION", "GameTools", "GAMEWORLD", "GPV", "Harvest4D", "INTRA-SPACE", "Landspotting", "MAKE-IT-FAB", "MARG", "Mofa", "OpenData", "PAMINA", "PathSpace", "Photo-Guide", "realreflect", "REPLICATE", "RESHADE", "Scanopy", "SCI_BIM", "ShapeAcquisition", "Skydome", "Superhumans", "TERAPOINTS", "Treelumination", "UrbanViz", "Visual Computing", "Wohnen 4.0", "WorldScale" ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Perception", "Rendering", "VR" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ADORJAN-2013-ASE", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "aichner-2016-sadf", "akan-vf", "albillos-2013-MA", "Ams25", "antes_sebastian-2026-msc", "antes-g", "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "arikan-thesis", "Arleo-2019-vis", "Artusi-2001-Col", "Artusi-2003-CCG", "Artusi-2003-Col", "Artusi-2003-Del", "ASCHL-2022-OTV", "AUER-2010-PPT3D", "ausserer-2026-baa", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2014-WiGr", "Auzinger-2015-IST", "auzinger-2015-phd", "auzinger-2015-utokyo", "auzinger-dissertation", "auzinger-thesis", "bagar_2008", "BAGAR-2010-LPB", "bagar2010", "balvan-g", "balvan-rsf", "BARSUKOV-2010-NEPC", "bauchinger-2007-mre", "Bauer_Dominik_2018_VR", "BAUER-2009-AFSS", "BAUER-2024-PWG", "BAUER-2025-PCW", "bayer_bernhard-2026-baa", "beck-2007-melk", "beham_2009.2009-EVS", "BEHAM-2014-RCR", "beleznai_csaba-2025-pr", "belic_dejan_pr", "Bernhard_Matthias_2014_VAC", "bernhard-2010-gph", "bernhard-2011-bmtf", "bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "birsak-2014-agtb", "birsak-2017-dpe", "birsak-2017-dpe", "Birsak-Michael-2012", "birsak-thesis", "birsak-thesis", "Birsak2018-SA", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "bodzenta-2026-baa", "Bogner-2008-MTh", "boindl_2013", "BOKSANSKY-2019-RTS", "BORZA-2012-Stellarium", "brandmair-2024-bind", "brandmair-2024-rust", "brandmair-2025-rub", "Brandorff_06_PON", "Brandorff_06_SKIN", "brenner_simon-2013-ba", "brugger-2020-tdp", "brugger-2020-tsdpbr", "brugger-2020-tsdpbr", "brunner_lukas_2022_ssb", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "Calatrava_2013_GPGPUSOA", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-thesis", "CHARALAMBOS-2007-HLOD", "charpenay-2013-PR", "charpenay-2014-sgn", "Che-2025", "CHIU-2008-PEN", "clemenz_2019_rosy_fields", "CORNEL-2010-VIS", "CORNEL-2014-AFRS", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "csecsy-fcd", "darovskikh_leonid-2025-prj", "dataset", "dataset-cat", "dataset-chair", "dataset-dragon", "dataset-duck", "dataset-ferris-wheel", "dataset-penguin", "dataset-strauss", "dataset-tramway", "dataset-viennacity", "daubner-2007-HDR", "deak-a3", "deix-2008-rcp", "dellmour-2013-grs", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuericht-2026-GPUCDR", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "RAOULZADEH-2026-STROKES2DEFORM", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", 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"sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" }, { "id": "Superhumans", "workgroup_id": "rend", "drupal_id": 4166, "drupal_path": "/research/projects/Superhumans", "name": "Superhumans - Walking Through Walls", "name_de": null, "short_title": "Superhumans", "website": null, "status": "active", "short_abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

\r\n", "abstract": "

In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.

\r\n", "start_date": "2019-09-01", "end_date": "2023-08-31", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:Superhumans", "type": "image/jpeg", "size": 96578, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Superhumans/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P32418-N31", "comment": "332.780,70 €" } ], "research_areas": [ "Geometry", "VR" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "leimer_2020-cag", "marin-2024-pcp", "parakkat-2024-ballmerge", "rait_alexius-2021-baa", "SCHUETZ-2020-MPC", "schuetz-2020-PPC" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Superhumans", "__class": "Project" }, { "id": "ShapeAcquisition", "workgroup_id": "rend", "drupal_id": 4173, "drupal_path": "/research/projects/ShapeAcquisition", "name": "Real-Time Shape Acquisition with Sensor-Specific Precision", "name_de": null, "short_title": "ShapeAcquisition", "website": null, "status": "active", "short_abstract": "Acquiring shapes of physical objects in real time and with guaranteed precision to the noise model of the sensor devices.", "abstract": "

The core idea in this project is to capture the shape of physical objects in real time, with guaranteed precision, and to reconstruct the shape boundaries with minimal geometry. An example application is to let untrained users acquire shapes using emerging mobile sensing devices such as Google’s Project Tango. The user moves the sensor around the object, guided by immediate visual feedback on the input sampling quality. The output is a topologically clean mesh consisting of just the vertices required to represent its features to the desired approximation. The real-time reconstruction enables numerous geometry-processing applications to be taken online, such as shape retrieval/matching, harvesting real-world geometry into a cloud, perspective photo correction, interactive modeling, augmented reality, physics simulation, or fabrication.

\r\n", "start_date": "2015-12-01", "end_date": "2020-11-30", "leader_id": 193, "logo": { "name": "logo.jpg", "path": "project:ShapeAcquisition", "type": "image/jpeg", "size": 20004, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ShapeAcquisition/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P24600-N23", "comment": null } ], "research_areas": [ "Geometry" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "forsythe-2016-ccm", "grossmann-2016-baa", "gruber_horst-2019-baa", "koeppel-2016-baa", "novak_martin-2018-baa", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger-2016-sgp", "pointner_michael-2017-baa", "Radwan_2021_Occ", "Radwan-2017-Occ", "reinwald-2017-baa", "schaffarz_2018-pra", "schartmueller_2018_baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ShapeAcquisition", "__class": "Project" }, { "id": "d4388", "workgroup_id": "rend", "drupal_id": 4388, "drupal_path": "/research/projects/Images2Mesh-Web", "name": "Photogrammetry made easy", "name_de": "Photogrammetrie einfach gemacht", "short_title": "Images2Mesh Web", "website": null, "status": "active", "short_abstract": null, "abstract": "

Dieses Projekt richtet sich an alle Menschen, die gerne etwas in der echten Welt einscannen und anderen Menschen als 3D-Modell zeigen wollen. Beispielsweise könnte ein Artist unterwegs eine interessante Skulptur finden und diese in ein Spiel einbauen oder als Miniatur ausdrucken. Raumplaner könnten z.B. eine Kreuzung einscannen, nach ihren Plänen verändern und diese damit besser kommunizieren.

", "start_date": "2020-12-01", "end_date": "2024-03-31", "leader_id": 1395, "logo": { "name": "logo.png", "path": "project:d4388", "type": "image/png", "size": 1173196, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d4388/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Modeling" ], "publications": [ "erler_2024_ppsurf", "erler_philipp-2017-phd", "pichler_2022_fro", "steinschorn-2023-p2m" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Images2Mesh-Web", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/erler_2024_ppsurf/", "__class": "Publication" }, { "id": "Grossfurtner-2023-paego", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Generating Aesthetic Plant Models from an Open Data Format of the Project for Sustainable Agroecosystems in Godot", "date": "2023-12", "abstract": "This bachelor's thesis explores the development of a plugin for the open-source game engine Godot 3.5, aimed at providing an easy way for procedurally creating pleasing plant visualizations, specifically in the frame of the Sustainable Agroecosystem project. This is achieved by importing data conforming to a predefined format that abstractly describes the structure of plant organisms. Upon import, the plugin generates 3D surfaces for the branching structures and employs instancing for rendering leaves efficiently. One of the key features of the plugin is its adaptive surface subdivision mechanism, which dynamically generates the surface at different levels of detail based on the proximity to the camera.\n\nThe plugin's implementation leverages Godot's GDPlugin feature to seamlessly integrate into the engine's workflow. The procedural generation of plant structures is achieved through algorithmic processes that translate \"tree skeletons\" into 3D surfaces. However, due to limitations inherent in Godot 3, the adaptive subdivision mechanism is implemented on the CPU. In tests, this resulted in the following: Exports of models in the highest level of detail yielded better performance than models with adaptive subdivision.\n\nThe thesis covers the design, implementation, and theory behind the plugin. An evaluation of the plugin's functionality and performance is conducted, highlighting its capability to dynamically adapt the mesh at runtime. Performance comparisons between the adaptive subdivision approach and using the exported surface are presented, revealing the issues with the implementation on the CPU.\n\nIn conclusion, the developed plugin presents a novel approach to procedurally generate and render complex plant structures within the Godot 3.5 game engine. It extends the capabilities of the engine in creating realistic virtual environments while addressing the challenges of adaptive subdivision on the CPU. The thesis explores the intricacies of integrating such plugins into game engines and opens avenues for further optimizations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser-img", "main_file": false, "use_in_gallery": false, "access": "hidden", "image_width": 741, "image_height": 1032, "name": "Grossfurtner-2023-paego-teaser-img.png", "type": "image/png", "size": 629380, "path": "Publication:Grossfurtner-2023-paego", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/Grossfurtner-2023-paego/Grossfurtner-2023-paego-teaser-img.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/Grossfurtner-2023-paego/Grossfurtner-2023-paego-teaser-img:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5302, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Moritz Leander", "lastname": "Großfurtner", "searchname": "Moritz Leander Großfurtner", "is_teacher": false, "name": "Moritz Leander Großfurtner", "publications": [ "Grossfurtner-2023-paego" ], "publications_first": [ "Grossfurtner-2023-paego" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5302", "__class": "Author" } ], "date_end": "2023-12", "date_start": "2021-11", "matrikelnr": "0271409", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_Mistelbauer_2013_CSR", "bagar2010", "bernhard-2010-gph", 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"wimmer-2023-acd", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Win25", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "WINKLER-2013-AMO", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Winkler-2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "WINKLER-2019-PDG", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "winklhofer_christoph-2013-RRMR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wolffhardt-2026-prj", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wonka-2000-VisP", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Wonka-2001-Ins", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Wonka-2003-Ins", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "WONKA-2006-GVS", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "yoo-chaeran-2025-pr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ZAU14", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "zeilinger_matthias-2020-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Zezulka_Matthias-2023-MatLabOptInterface", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Zezulka-2024-FTS", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Zezulka-2025-NRL", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Zezulka-2026-FGTS", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Zezulka-2026-GridThermalSim", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "zhang-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ZL_2011_IVIG", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "akan-vf", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", 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Following the footsteps of ε-sampling, which was originally proposed in the context of curve reconstruction to offer provable topological guarantees [ABE98] under quantifiable bounds, we propose an arbitrarily precise ε-sampling algorithm for sampling smooth planar curves (with a prior bound on the minimum feature size of the curve). This paper not only introduces the first such algorithm which provides user-control and quantifiable precision but also highlights the importance of such a sampling process under two key contexts: 1) To conduct a first study comparing theoretical sampling conditions with practical sampling requirements for reconstruction guarantees that can further be used for analysing the upper bounds of ε for various reconstruction algorithms with or without proofs, 2) As a feature-aware sampling of vector line art that can be used for applications such as coloring and meshing. 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/withalm_brigitte-2022-baa/", "__class": "Publication" }, { "id": "steinschorn-2023-p2m", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Reconstruction for a photogrammetry webservice", "date": "2023-08", "abstract": "Subject of this student project is the reconstruction and evaluation part for a photogrammetry webservice. It consists of Screened Poisson Surface Reconstruction, test scenes and metrics.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Pix2Model Evaluation Example", "filetitle": "pix2model_eval", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1914, "image_height": 775, "name": "steinschorn-2023-p2m-pix2model_eval.png", "type": "image/png", "size": 971490, "path": "Publication:steinschorn-2023-p2m", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/steinschorn-2023-p2m/steinschorn-2023-p2m-pix2model_eval.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/steinschorn-2023-p2m/steinschorn-2023-p2m-pix2model_eval:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1757, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Florian", "lastname": "Steinschorn", "searchname": "Florian Steinschorn", "is_teacher": false, "name": "Florian Steinschorn", "publications": [ "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter" ], "publications_first": [ "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1757", "__class": "Author" } ], "date_end": "2023-08", "date_start": "2021-06", "matrikelnr": "1227109", "supervisor": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", "firstname": "Philipp", "lastname": "Erler", "searchname": "Philipp Erler", "is_teacher": false, "name": "Philipp Erler", "publications": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout", "ilcik-2021-xmas" ], "publications_first": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout" ], "project_leader": [ "d4388" ], "publication_field": [ { "publ_id": "clemenz_2019_rosy_fields", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "clemenz_2019_rosy_fields", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "erler_2024_ppsurf", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2020-p2s", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2025-lidarscout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hofer_kerstin-2023-sketch2model", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kapferer_2021_advancing", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pichler_2022_fro", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "riegler_2020_framework", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2023-p2m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-par", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-parameter", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1395", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", 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"Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", 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"id": "d4388", "workgroup_id": "rend", "drupal_id": 4388, "drupal_path": "/research/projects/Images2Mesh-Web", "name": "Photogrammetry made easy", "name_de": "Photogrammetrie einfach gemacht", "short_title": "Images2Mesh Web", "website": null, "status": "active", "short_abstract": null, "abstract": "

Dieses Projekt richtet sich an alle Menschen, die gerne etwas in der echten Welt einscannen und anderen Menschen als 3D-Modell zeigen wollen. Beispielsweise könnte ein Artist unterwegs eine interessante Skulptur finden und diese in ein Spiel einbauen oder als Miniatur ausdrucken. Raumplaner könnten z.B. eine Kreuzung einscannen, nach ihren Plänen verändern und diese damit besser kommunizieren.

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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In this poster, we propose an extension to the proximity graph introduced in [MOW22] to three-dimensional models. We use the spheres-of-influence (SIG) proximity graph restricted to the 3D Delaunay graph to compute connectivity between points. Our approach shows a better encoding of the connectivity in relation to the ground truth than the k-nearest neighborhood (kNN) for a wide range of k values, and additionally, it is parameter-free. Our result for this fundamental task offers potential for many applications relying on kNN, e.g., improvements in normal estimation, surface reconstruction, motion planning, simulations, and many more.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "hidden", "image_width": 455, "image_height": 200, "name": "marin-2023-pic-image.png", "type": "image/png", "size": 20480, "path": "Publication:marin-2023-pic", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/marin-2023-pic/marin-2023-pic-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/marin-2023-pic/marin-2023-pic-image:thumb{{size}}.png" }, "sync_repositum_override": "booktitle", "repositum_presentation_id": null, "authors": [ { "id": 1848, "drupal_id": 3143, "orcid_id": "0000-0002-8812-9719", "website": 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"lecturer": [ { "id": 1848, "drupal_id": 3143, "orcid_id": "0000-0002-8812-9719", "website": "https://www.cg.tuwien.ac.at/staff/DianaMarin", "firstname": "Diana", "lastname": "Marin", "searchname": "Diana Marin", "is_teacher": false, "name": "Diana Marin", "publications": [ "ehlers-2024-vgs", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "ohrhallinger_stefan-2024-inv" ], "publications_first": [ "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis" ], "project_leader": [], "publication_field": [ { "publ_id": "brunner_lukas_2022_ssb", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Komon2022", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "marin-2022-sig", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "marin-2022-sigdt", "field_id": 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/marin-2023-pic/", "__class": "Publication" }, { "id": "hofer_kerstin-2023-sketch2model", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Sketch to 3d-Model using Deep Learning and Differentiable Rendering", "date": "2023-03-03", "abstract": "Deriving 3D models from sketches has been a relevant research topic for years now, mainly due to its potential to simplify the realization of ideas and drafts for certain professions like artists, engineers and designers. With the raise of neural networks, new methods start to form utilizing the learning capability of those networks. One such method is the application of differentiable rendering, where a base mesh is deformed until the difference between the differentiable renderings and the target image is reasonably small. However, those target images, e.g., normal or depth maps, are not inherently available to the system, since the only input is a sketch. Therefore, intermediate representations predicted from the sketch need to be generated, that provide the required information.\n\nThe aim of this thesis is to provide a an end-to-end framework that reconstructs 3d models from 2d sketches using intermediate depth and normal representations and differentiable rendering. In addition to that, the topology of the sketch is determined and a respective base mesh is used for the mesh deformation. By comparing this setup to an established network as well as conducting an ablation study to reveal the effects the improvements have, the system and its limitations are evaluated. This will determine if the proposed optimisations facilitate input generalisability beyond class/object restrictions and improve mesh quality.", "authors_et_al": false, "substitute": null, "main_image": { "description": "General system overview. From a seeded user sketch, the silhouette image, the normal and depth maps are translated and a base mesh is determined. Using those, a differentiable renderer is used in order to predict a 3d model.", "filetitle": "Method", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2206, "image_height": 993, "name": "hofer_kerstin-2023-sketch2model-Method.png", "type": "image/png", "size": 326093, "path": "Publication:hofer_kerstin-2023-sketch2model", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Method.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Method:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5280, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Kerstin", "lastname": "Hofer (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "searchname": "Kerstin Hofer (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "is_teacher": false, "name": "Kerstin Hofer (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "publications": [ "hofer_kerstin-2023-sketch2model" ], "publications_first": [ "hofer_kerstin-2023-sketch2model" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5280", "__class": "Author" } ], "co_supervisor": [ { "id": 5281, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Clemens", "lastname": "Havas (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "searchname": "Clemens Havas (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "is_teacher": false, "name": "Clemens Havas (Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria)", "publications": [], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "hofer_kerstin-2023-sketch2model", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5281", "__class": "Author" } ], "date_end": "2023-03-03", "date_start": "2022-11", "diploma_examina": "2023-05-03", "matrikelnr": "2010695019", "note": "Thesis created in cooperation with Department Creative Technologies, University of Applied Sciences Salzburg, Salzburg, Austria", "open_access": "yes", "supervisor": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", "firstname": "Philipp", "lastname": "Erler", "searchname": "Philipp Erler", "is_teacher": false, "name": "Philipp Erler", "publications": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout", "ilcik-2021-xmas" ], "publications_first": [ "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2025-lidarscout" ], "project_leader": [ "d4388" ], "publication_field": [ { "publ_id": "clemenz_2019_rosy_fields", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "clemenz_2019_rosy_fields", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "erler_2024_ppsurf", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2020-p2s", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "erler-2025-lidarscout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hofer_kerstin-2023-sketch2model", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kapferer_2021_advancing", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pichler_2022_fro", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "riegler_2020_framework", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2023-p2m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-par", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinschorn-2025-parameter", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1395", "__class": "Author" } ], "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "Fuericht-2026-GPUCDR", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasch-2016-imgses", "RASOULZADEH-2026-PREDICTING", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "akan-vf", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "KOEPPEL-2025-Nearfield", "Koeppl-2023-DLO", "Komon2022", "Konev-FCV2018", "Kovacs_2017", "kovacs-2025-pf", "KREUZER-2015-DPA", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "KROESL-2020-SVI", "kroesl-2020-XREye", "KUE11", "Kugler-2021", "Lan25", "leopold-2019-vox", "Liang-2023-TVR", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "maier-2024-3vo", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "Mazza_2021_05", "Meier_2024_WIALT", "MEINDL-2015-OSR", "metzger-2024-smv", "mindek-2017-marion", "mindek-xmas-card-2016", "murturi_PGG", "muth-2026-clouds", "neumann-2006-gamma", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "panfili-2019-VAVR", "panfili-2021-myop", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "PETER-2023-PSW", "pichler_2022_fro", "pirraku-f", "pistellato-2023-elp", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "preiner_2010_GIPC", "preiner_2017_phd", "preiner11IR", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "probst-2023-para", "prost-2016-molecule", "PROST-2017-RTL", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "radax-2008-ir", "Rainer_2017", "Rait2022", "Reisner_Irene_2013_R3D", "reznicek-2020-fpgaray", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "SCHOBER-2006-IVSA", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "schwaerzler_2018_phd", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "Semmelrath-2022-IRS", "seyr-2026-shwizard", "silvana_2014", "sippl_tobias_2017_WPC", "SIPPL-2017-POS", "sorger-2015-litevis", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "STEINLECHNER-2019-ICT", "STREICHER-2022-DSLS", "STU-SR-25", "Sturn-2013-ST", "Szabo-2018-DA", "tatzgern-2020-sst", "Thann_2019_01", "themmer-2018-fbx", "tobler97_hsdasr", "TR 193-02-2019-4", "TR 193-2-2019-4", "TR-186-2-02-04", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "traxler-1997-TRA", "Tucek_2018", "Tucek_Tom-2016-aai", "ulschmid-2025-apc", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "wagner-2024-par", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weinzierl_heigl-2017-wh14", "werdermann-va", "WESSNER-2019-PCW", "wiesinger_2020_odpr", "wiesinger-2023-gcg", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-VCCG", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "Win25", "winklmueller-2025-ims", "wonka-2000-VisP", "Wonka-2001-Ins", "WONKA-2006-GVS", "x-mas-2013", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "zotti-2005-lum", "zotti-2006-pla", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "deep learning", "single-view model generation", "topology", "differentiable rendering", "2.5d intermediate representation" ], "weblinks": [ { "href": "https://github.com/Kerstin08/Sketch-to-3d-Model", "caption": "Source Code", "description": "Repository on Github ", "main_file": 1 } ], "files": [ { "description": "General system overview. From a seeded user sketch, the silhouette image, the normal and depth maps are translated and a base mesh is determined. Using those, a differentiable renderer is used in order to predict a 3d model.", "filetitle": "Method", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2206, "image_height": 993, "name": "hofer_kerstin-2023-sketch2model-Method.png", "type": "image/png", "size": 326093, "path": "Publication:hofer_kerstin-2023-sketch2model", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Method.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Method:thumb{{size}}.png" }, { "description": "Master's Thesis by Kerstin Hofer: Sketch to 3d Model", "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "hofer_kerstin-2023-sketch2model-Thesis.pdf", "type": "application/pdf", "size": 18941567, "path": "Publication:hofer_kerstin-2023-sketch2model", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/hofer_kerstin-2023-sketch2model/hofer_kerstin-2023-sketch2model-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "rend", "drupal_id": 1355, "name": "Rendering and Modeling", "website": "https://www.cg.tuwien.ac.at/group/Rendering-and-Modeling", "projects": [ "3DSpatialization", "CROSSMOD", "d10070", "d10169", "d10214", "d10381", "d4307", "d4314", "d4342", "d4386", "d4388", "d4559", "d4729", "d4958", "d4984", "d9259", "d9493", "d9691", "Desiree", "EU U-CREATE", "EU Virtual Showcases", "EVOCATION", "GameTools", "GAMEWORLD", "GPV", "Harvest4D", "INTRA-SPACE", "Landspotting", "MAKE-IT-FAB", "MARG", "Mofa", "OpenData", "PAMINA", "PathSpace", "Photo-Guide", "realreflect", "REPLICATE", "RESHADE", "Scanopy", "SCI_BIM", "ShapeAcquisition", "Skydome", "Superhumans", "TERAPOINTS", "Treelumination", "UrbanViz", "Visual Computing", "Wohnen 4.0", "WorldScale" ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Perception", "Rendering", "VR" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ADORJAN-2013-ASE", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "aichner-2016-sadf", "akan-vf", "albillos-2013-MA", "Ams25", "antes_sebastian-2026-msc", "antes-g", "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "arikan-thesis", "Arleo-2019-vis", "Artusi-2001-Col", "Artusi-2003-CCG", "Artusi-2003-Col", "Artusi-2003-Del", "ASCHL-2022-OTV", "AUER-2010-PPT3D", "ausserer-2026-baa", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2014-WiGr", "Auzinger-2015-IST", "auzinger-2015-phd", "auzinger-2015-utokyo", 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"brandmair-2024-rust", "brandmair-2025-rub", "Brandorff_06_PON", "Brandorff_06_SKIN", "brenner_simon-2013-ba", "brugger-2020-tdp", "brugger-2020-tsdpbr", "brugger-2020-tsdpbr", "brunner_lukas_2022_ssb", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "Calatrava_2013_GPGPUSOA", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-thesis", "CHARALAMBOS-2007-HLOD", "charpenay-2013-PR", "charpenay-2014-sgn", "Che-2025", "CHIU-2008-PEN", "clemenz_2019_rosy_fields", "CORNEL-2010-VIS", "CORNEL-2014-AFRS", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "csecsy-fcd", "darovskikh_leonid-2025-prj", "dataset", "dataset-cat", "dataset-chair", "dataset-dragon", "dataset-duck", "dataset-ferris-wheel", "dataset-penguin", "dataset-strauss", "dataset-tramway", "dataset-viennacity", "daubner-2007-HDR", "deak-a3", "deix-2008-rcp", "dellmour-2013-grs", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuericht-2026-GPUCDR", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", 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"https://www.cg.tuwien.ac.at/research/publications/2023/rubik_michael-2022-baa/rubik_michael-2022-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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However, it introduces the challenge of streaming rendered data over a network in a manner that is robust to latency and potential dropouts. Current approaches range from streaming transmitted video and correcting it on the client---which fails in the presence of disocclusion events---to solutions where the server sends geometry and all rendering is performed on the client. To balance the competing goals of disocclusion robustness and minimal client workload, we introduce QuadStream, a new streaming technique that reduces motion-to-photon latency by allowing clients to render novel views on the fly and is robust against disocclusions. Our key idea is to transmit an approximate geometric scene representation to the client which is independent of the source geometry and can render both the current view frame and nearby adjacent views. Motivated by traditional macroblock approaches to video codec design, we decompose the scene seen from positions in a view cell into a series of view-aligned quads from multiple views, or QuadProxies. By operating on a rasterized G-Buffer, our approach is independent of the representation used for the scene itself. Our technical contributions are an efficient parallel quad generation, merging, and packing strategy for proxy views that cover potential client movement in a scene; a packing and encoding strategy allowing masked quads with depth information to be transmitted as a frame coherent stream; and an efficient rendering approach that takes advantage of modern hardware capabilities to turn our QuadStream representation into complete novel views on thin clients. According to our experiments, our approach achieves superior quality compared both to streaming methods that rely on simple video data and to geometry-based streaming.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 500, "image_height": 281, "name": "hladky-2022-QS-teaser.jpg", "type": "image/jpeg", "size": 176021, "path": "Publication:hladky-2022-QS", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/hladky-2022-QS/hladky-2022-QS-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/hladky-2022-QS/hladky-2022-QS-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,location,lecturer,event,date_to,date_from", "repositum_presentation_id": null, "authors": [ { "id": 5184, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Jozef", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", 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"pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "akan-vf", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", 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In this area, we focus on user experiences and rendering algorithms for virtual reality environments, including methods to navigate and collaborate in VR, foveated rendering, exploit human perception and simulate visual deficiencies.

", "abstract": "

In this area, we focus on user experiences and rendering algorithms for virtual reality environments, including methods to navigate and collaborate in VR, foveated rendering, exploit human perception and simulate visual deficiencies.

", "website": "https://www.cg.tuwien.ac.at/research/area/VR", "teaser": { "name": "teaser.jpg", "path": "research_area:VR", "type": "image/jpeg", "size": 191119, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/VR/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "adolf-2019-jug", "Alharbi_2021", "Bayer_Alexander_2021_FTiVR", "Erhardt_2025_Scutes", "gall-2025-marv", "Goellner_2019-ABC", "gramegna-rfr", "hladky-2022-QS", "huber-2025-eed", "huber-2025-esl", "Kan_Peter-2021-MDPI", "kan-2019-dli", "Kathi-2018-VRB", "Kovacs_2020", "Kroesl_2020_11_09", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "medeiros-2023-gwf", "Mirzaei_Mohammadreza_2020-EVR", "Mortezapoor2021ssc", "panfili-2019-VAVR", "perl_oskar_2021_DVR", "pirch_2021_VRN", "podkosova_2022_bimflexi-vr", "Prossenitsch_2019-1", "reimer-2020-CBG", "reimer-2021-CVR", "Schoenauer_2020_POI", "schuller_reichl-2019-avt", "Sebernegg2020", "sorger-2021-egonet", "Sprung_2021", "Vasylevska2020VRB", "Vonach021", "walchhofer_ar_flowmaps", "walchhofer-tso" ], "projects": [ "BimFlexi", "d4322", "d9275", "EU U-CREATE", "EvaluARte", "MARG", "Superhumans" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=VR", "__class": "ResearchArea" } ], "keywords": [ "streaming", "real-time rendering", "virtual reality" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 500, "image_height": 281, "name": "hladky-2022-QS-teaser.jpg", "type": "image/jpeg", "size": 176021, "path": "Publication:hladky-2022-QS", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/hladky-2022-QS/hladky-2022-QS-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/hladky-2022-QS/hladky-2022-QS-teaser:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/hladky-2022-QS/", "__class": "Publication" }, { "id": "marin-2022-sigdt", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/175713", "title": " SIGDT: 2D Curve Reconstruction", "date": "2022-10-05", "abstract": "Determining connectivity between points and reconstructing their shape boundaries are long-standing problems in computer graphics. One possible approach to solve these problems is to use a proximity graph. We propose a new proximity graph computed by intersecting the to-date rarely used proximity-based graph called spheres-of-influence graph (SIG) with the Delaunay triangulation (DT). We prove that the resulting graph, which we name SIGDT, contains the piece-wise linear reconstruction for a set of unstructured points in the plane for a sampling condition superseding current bounds and capturing well practical point sets' properties. As an application, we apply a dual of boundary adjustment steps from the CONNECT2D algorithm to remove the redundant edges. We show that the resulting algorithm SIG-CONNECT2D yields the best reconstruction accuracy compared to state-of-the-art algorithms from a recent comprehensive benchmark, and the method offers the potential for further improvements, e.g., for surface reconstruction.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 7066, "image_height": 3125, "name": "marin-2022-sigdt-Teaser.png", "type": "image/png", "size": 457323, "path": "Publication:marin-2022-sigdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Teaser:thumb{{size}}.png" }, "sync_repositum_override": "issn", "repositum_presentation_id": null, "authors": [ { "id": 1848, "drupal_id": 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"steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" } ], "keywords": [ "Curve reconstruction", "Spheres-of-influence graph" ], "weblinks": [ { "href": "https://diglib.eg.org/handle/10.1111/cgf14654", "caption": "Paper", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "marin-2022-sigdt-Paper.pdf", "type": "application/pdf", "size": 2877751, "path": "Publication:marin-2022-sigdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Paper:thumb{{size}}.png" }, { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 7066, "image_height": 3125, "name": "marin-2022-sigdt-Teaser.png", "type": "image/png", "size": 457323, "path": "Publication:marin-2022-sigdt", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/marin-2022-sigdt-Teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/marin-2022-sigdt/", "__class": "Publication" }, { "id": "elagrod_ahmed-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Immersive Redesign", "date": "2022-09-05", "abstract": "With scanning technologies and the processing power of computers increasing it is getting easier\nto scan the surrounding area and upload a 3D model of it. Nowadays mobile phones and drones\nare capable of doing that. However, the results most likely are not as good as dedicated scanners.\nTo offer people an option to explore their scanned objects my colleague Manuel Keilman and\nI wrote a software with which users can upload multiple point clouds. Those point clouds can\nthen be modified by adding, deleting, or moving parts of it. Our primary target is point clouds\nof street scenes. We selected an existing classification algorithm called GraND-Net [13] to\nidentify objects of the scene. Since the classification algorithm does not cluster the classes a\nseparate algorithm for that was needed. That is why we use DBScan [15] in order to distinguish\ndifferent objects of the same class. Both steps are done before starting the application since they\nonly have to be done once. The benefit of grouping points with similar features is that users\ndo not have to manually select everything which improves the usability of our software. After\nclassifying as well as clustering users can upload their point clouds and then select objects in\norder to modify them. Mistakes tend to happen which is why our software also offers users the\noption to manually classify whatever they want. All of that should make it easier for users to\nanalyze and modify their point clouds.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 556, "image_height": 213, "name": "elagrod_ahmed-baa-image.png", "type": "image/png", "size": 225625, "path": "Publication:elagrod_ahmed-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/elagrod_ahmed-baa/elagrod_ahmed-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/elagrod_ahmed-baa/elagrod_ahmed-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5287, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Ahmed", "lastname": "El Agrod", "searchname": "Ahmed El Agrod", "is_teacher": false, "name": "Ahmed El Agrod", "publications": [ "elagrod_ahmed-baa" ], "publications_first": [ "elagrod_ahmed-baa" ], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5287", "__class": "Author" } ], "date_end": "2022-09-05", "date_start": "2022-01-15", "matrikelnr": "11811340", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_Mistelbauer_2013_CSR", "bagar2010", "bernhard-2010-gph", "bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "birsak-2013-sta", "birsak-2014-agtb", "birsak-2017-dpe", "Bittner-2001-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brugger-2020-tdp", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "celarek-2025-d3g", "CHARALAMBOS-2007-HLOD", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "dataset-viennacity", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "erler_2024_ppsurf", "erler-2020-p2s", "erler-2025-lidarscout", "fink-2012-cg1", "fink-2013-cag", "freude_2020_rs", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "GRELAUD-2009-EPA", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2012_PSP", "Habel_LSN_2011", "Habel-2010-EIN", "hafner-2015-onff", "hecher-2014-MH", "HECHER-2017-HDY", "Honic_2021", "honic-2020-w78", "HU-2017-ETM", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2016-cescg", "ilcik-2016-cmssg", "JAHRMANN-2013-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ISTAR", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "Jimenez_SSS_2015", "Kathi-2018-VRB", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "klaffenboeck-2024-rva", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2011-CBCM", "KOCH-2021-GVS", "koenigsberger-2024-msu", "kovacs-2023-ttm", "KREUZER-2015-DPA", "kristmann-2026-vtc", "Kroesl_2020_11_09", "kroesl-2017-LiteMaker", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2020-XREye", "leimer_2017_rbpesc", "leimer-2016-rpe", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "MANTLER-2007-DMBBC", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "matt2011", "MATTAUSCH-2006-AVC", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "musialski-2015-souos", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger-2016-sgp", "OTEPKA-2020-PPC", "panfili-2021-myop", "pistellato-2023-elp", "preiner_2010_GIPC", "preiner_2012_AS", "Preiner_2019", "preiner2014clop", "PUEYO-2019-SCL", "PURGATHOFER-2006-IHB", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "reisinger-2023-iad", "ROEGNER-2015-IBR", "roth_vdi", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "santos-2017-dacge", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer2011c", "scherzer2011d", "SCHUETZ-2015-HQP", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "SSMW09", "stappen_SteFAS", "steiner_2016_isad", "STEINLECHNER-2019-APS", "STURN-2013-LGI", "STURN-2013-LSI", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "TR 193-02-2019-4", "TR 193-2-2019-4", "TR-186-2-02-04", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-12-01", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "wallner-2015-ModelingRoutinization", "WEBER-2015-PRA", "Wimmer-1996-ITB", "Wimmer-1997-ITT", "Wimmer-1998-Fas", "Wimmer-1998-SMO", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-CCL", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "Wimmer-2006", 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"https://www.cg.tuwien.ac.at/research/publications/2022/elagrod_ahmed-baa/elagrod_ahmed-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "WorldScale", "workgroup_id": "rend", "drupal_id": 4158, "drupal_path": "/research/projects/WorldScale", "name": "Modeling the World at Scale", "name_de": "Modellierung der Welt nach Maß", "short_title": "WorldScale", "website": null, "status": "active", "short_abstract": "Vision: reconstruct a model of the world that permits online level-of-detail extraction.", "abstract": "

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

\r\n", "start_date": "2020-05-01", "end_date": "2026-04-30", "leader_id": 948, "logo": { "name": "logo.jpg", "path": "project:WorldScale", "type": "image/jpeg", "size": 64953, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "WWTF", "contract_number": "ICT19-009", "comment": "€ 578.450" } ], "research_areas": [ "Geometry" ], "publications": [ "antes_sebastian-2026-msc", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "elagrod_ahmed-baa", "fitzinger_andreas-daa", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hoffer-toth-com", "holom_2025-prj", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "karampekios_anastasios-prj", "kazda-tmd", "knoetzl_alexander-2025-prj", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "lang_jakob-2022-baa", "lazarevic-tci", "leutschacher_2025_prj", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "pakkanen-2026-prj", "parakkat-2024-ballmerge", "perzi_marvin-2026-baa", "pointner_simon-2022-maa", "proelss-bdp", "prohaska_julia-2023-baa", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "resch_martin-2026-baa", "rozanics-lsf", "rubik_michael-2022-baa", "schrammel_sebastian_baa", "schulz-faf", "seisenbacher-cyclesafely", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steinheber-2024-oto", "steinschauer-2020-baa", "telaar_sina-2026-baa", "trenovatz-lpd", "tumpach_barbara-pra", "ulschmid-2026-naadf", "vasiljevic-gpc", "wagentristl_stefan-2026-baa", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wildt-tci", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa" ], "url": "https://www.cg.tuwien.ac.at/research/projects/WorldScale", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/elagrod_ahmed-baa/", "__class": "Publication" }, { "id": "Vucenovic_2022", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Differential Rendering for Computed Tomography Reconstruction", "date": "2022-09-04", "abstract": "The recently achieved differentiability of path-tracing algorithms, which are the standard for generating photo-realistic images, opens up optimization possibilities for the 3Dreconstruction of an object using images acquired by X-ray scans. The reconstruction is accomplished by ”inverting the rendering pipeline”, which in practice means obtaining 3D\nscene parameters, such as volumetric data, from 2D images. The images act as a reference in our algorithm, which is optimizing the scene parameters until the image acquired\nby our rendered scene minimally differs from the reference image. In this publication, we represent a proof-of-concept and early experiments for differential rendering for CT\nreconstruction. Our implementation is able to successfully reconstruct the geometry and volume of specimens, using only images acquired from a software-simulated X-ray scan. 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"wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/Vucenovic_2022/", "__class": "Publication" }, { "id": "SCHUETZ-2022-PCC", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/193255", "title": "Software Rasterization of 2 Billion Points in Real Time", "date": "2022-07", "abstract": "We propose a software rasterization pipeline for point clouds that is capable of brute-force rendering up to two billion points in real time (60fps). Improvements over the state of the art are achieved by batching points in a way that a number of batch-level optimizations can be computed before rasterizing the points within the same rendering pass. These optimizations include frustum culling, level-of-detail rendering, and choosing the appropriate coordinate precision for a given batch of points directly within a compute workgroup. Adaptive coordinate precision, in conjunction with visibility buffers, reduces the number of loaded bytes for the majority of points down to 4, thus making our approach several times faster than the bandwidth-limited state of the art. Furthermore, support for LOD rendering makes our software-rasterization approach suitable for rendering arbitrarily large point clouds, and to meet the increased performance demands of virtual reality rendering. 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"Association for Computing Machinery (ACM)", "volume": "5", "research_areas": [ { "id": "Geometry", "drupal_id": 4129, "name": "Geometry Processing", "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "kloos-2026-icv", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-pcp", "marin-2024-sing", "markovich_aleksandar-2022-maa", "mayer_luiz-2026-baa", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "mazza-2012-bakk", "micu_2025-prj", "miklautsch_florian-baa", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-sur", "musialski-2013-surcgf", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "neumann-sfd", "novak_martin-2018-baa", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2019-xms", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-stefan-2012-the", "pakkanen-2026-prj", "pegrisch_2018_uvs", "perzi_marvin-2026-baa", "pichler_2022_fro", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "akan-vf", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", 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Our data fall into a category too large to be rendered directly at full resolution, but small enough to fit into GPU memory without pre-filtering and data streaming. We present the real-world use case of unfiltered flood simulation data of such medium scale that need to be visualized in real time for scientific purposes. Our solution facilitates compute shaders to maintain a guaranteed watertight triangulation in GPU memory that approximates the interpolated heightfields with view-dependent, continuous levels of detail. In each frame, the triangulation is updated incrementally by iteratively refining the cached result of the previous frame to minimize the computational effort. In particular, we minimize the number of heightfield sampling operations to make adaptive and higher-order interpolations viable options. We impose no restriction on the number of subdivisions and the achievable level of detail to allow for extreme zoom ranges required in geospatial visualization. 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"Loeffelmann-1998-Enh", "Loeffelmann-1998-EVC", "Loeffelmann-1998-SMURF", "Loeffelmann-1998-VDS", "Loeffelmann-1998-Vis", "Loeffelmann-1998-Visu", "Loeffelmann-1999-SMU", "malik-2007-FP", "malik-2009-CVFA", "malik-2010-cvp", "manylands_award", "Matkovic-2002-Pro", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Meinhart-1998-Tun", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Milik-1997-GMMO", "Milik-1998-Geo", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2015-mc", "mindek-2017-dsn", "mindek-2017-marion", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Morar_2012_ISB", "Mroz-1998-Bri", "Mroz-1998-Sel", "Mroz-1998-SelX", "Mroz-1999-Adv", "Mroz-1999-IHQ", "Mroz-1999-MIP", "Mroz-1999-Real", "Mroz-1999-ReaX", "Mroz-2000-Int", "Mroz-2000-Mas", 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"TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-13", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "tretyak-2025-tacmedvr", "Troidl_2022", "Tsoi-2000-Ada", "Vad_Viktor_2015_RVV", "vad_viktor-2017-WVE", "vaico", "Vilanova-1999-Vir", "Vilanova-1999-VirX", "Vilanova-2000-CAT", "Vilanova-2000-Cyl", "Vilanova-2000-VCF", "Vilanova-2001-Non", "Vilanova-2001-Per", "Vilanova-2001-VCU", "Vilanova-2001-Vir", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "Viola-2003-NON", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", 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"Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", "Groeller-1995-IED", "groeller-1995-inter", "groeller-1995-lok", "groeller-1995-mod", "groeller-1995-non", "Groeller-1995-SDC", "groeller-1995-vis", "Groeller-1998-VAD", "Groeller-1998-VDS", "Groeller-2001-IDV", "groeller-2002-anw", "Groeller-2002-Ins", "groeller-2002-med", "groeller-2002-wiss", "groeller-2003-fea", "groeller-2003-med", "groeller-2003-scie", "groeller-2003-vol", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-abs", "groeller-2005-foc", "groeller-2005-imp", "groeller-2005-impo", "groeller-2005-sma", "groeller-2005-smar", "groeller-2005-volg", "groeller-2006-cgf", "groeller-2006-civ", "groeller-2006-ivt", "groeller-2006-tvcg", "groeller-2007-csu", "groeller-2007-fci", "groeller-2007-mva", "groeller-2007-vis", "groeller-2007-visII", "groeller-2007-vws", "groeller-2008-att2", "groeller-2008-How", "groeller-2008-hsp", "groeller-2008-irs", "groeller-2008-kav2", "groeller-2008-kav3", "groeller-2008-kav4", "groeller-2008-lsy", "Groeller-2010-CVC", "groeller-2010-How", "Groeller-2010-IFI", "Groeller-2010-IVVI", "groeller-2010-PTT", "Groeller-2011-HSH", "Groeller-2017-AMOS", "Groeller-2017-IVAMCS", "groeller-2022-iva", "groeller-2022-iva-1", "groeller-2022-ivd", "groeller-2023-ivd", "groeller-2023-siv", "groeller-2023-siv-1", "groeller-2023-siv-2", "groeller-2023-tfo", "groeller-2024-cui", "groeller-cvc-2009", "groeller-scv-2009", "groeller-svo-2009", "groeller-vks-2009", "Groller_2021-12-03", "Grorller-2010-IVV", "purgathofer-1988-using" ], "project_leader": [ "AngioVis", "AutARG", "avr", "d10027", "d10162", "d10164", "d10489", "d4328", "d4335", "d4534", "d9275", "d9671", "d9951", "diagvis", "KASI", "ManyViews", "NeuroViewer", "ProKeyAnim", "PVG", "Semantic Steering", "Sim-CT", "Smart-CT", "ViMaL", "VISAR" ], "publication_field": [ { "publ_id": "2015-image-coll", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "2017-kouril-illcell", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "alsallakh-2009-iva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "altendorfer-2008-vts", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "amirkhanov-2012-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "amirkhanov-2021-diss", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ammer-2008-lst", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "AndreUrsits_2013_APP", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Artner-2005-Thesis", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "audioflow", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "balabanian-2009-mav", "field_id": 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The VRVis K1 Research Center is the leading application oriented research center in the area of virtual reality (VR) and visualization (Vis) in Austria and is internationally recognized. You can find extensive Information about the VRVis-Center here

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The VRVis K1 Research Center is the leading application oriented research center in the area of virtual reality (VR) and visualization (Vis) in Austria and is internationally recognized. You can find extensive Information about the VRVis-Center here

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Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.

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"20.500.12708/188182", "title": "Gaussian Mixture Convolution Networks", "date": "2022-04", "abstract": "This paper proposes a novel method for deep learning based on the analytical convolution of multidimensional Gaussian mixtures.\nIn contrast to tensors, these do not suffer from the curse of dimensionality and allow for a compact representation, as data is only stored where details exist.\nConvolution kernels and data are Gaussian mixtures with unconstrained weights, positions, and covariance matrices.\nSimilar to discrete convolutional networks, each convolution step produces several feature channels, represented by independent Gaussian mixtures.\nSince traditional transfer functions like ReLUs do not produce Gaussian mixtures, we propose using a fitting of these functions instead.\nThis fitting step also acts as a pooling layer if the number of Gaussian components is reduced appropriately.\nWe demonstrate that networks based on this architecture reach competitive accuracy on Gaussian mixtures fitted to the MNIST and ModelNet data sets.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1500, "image_height": 1367, "name": "celarek-2022-gmcn-teaser.png", "type": "image/png", "size": 720960, "path": "Publication:celarek-2022-gmcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/celarek-2022-gmcn/celarek-2022-gmcn-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/celarek-2022-gmcn/celarek-2022-gmcn-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1013, "drupal_id": 613, "orcid_id": "0009-0006-8571-4150", "website": "https://www.cg.tuwien.ac.at/staff/AdamCelarek", "firstname": "Adam", "lastname": "Celarek", "searchname": "Adam Celarek", "is_teacher": false, 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"https://www.cg.tuwien.ac.at/staff/BernhardKerbl", "firstname": "Bernhard", "lastname": "Kerbl", "searchname": "Bernhard Kerbl", "is_teacher": false, "name": "Bernhard Kerbl", "publications": [ "cardoso-2022-rtpercept", "celarek-2022-gmcn", "celarek-2025-d3g", "goel-2024-rdr", "hladky-2022-QS", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kerbl-2024-ah3", "murturi_PGG", "papantonakis-2024-rmf", "roth_vdi", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "stappen_SteFAS", "tatzgern-2020-sst", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "voglreiter-2023-tro" ], "publications_first": [ "kerbl_2021_hdg", "kerbl-2022-cuda", "kerbl-2022-trienc", "kerbl-2024-ah3" ], "project_leader": [], 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"macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "mao-2026-rsd", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", 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"scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2026-shwizard", "SIETZEN-2017-BBO", "silvana_2014", 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"telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" }, { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" }, { "id": "3DSpatialization", "workgroup_id": "rend", "drupal_id": 4156, "drupal_path": "/research/projects/3DSpatialization", "name": "Smart Communities and Technologies: 3D Spatialization", "name_de": null, "short_title": "3DSpatialization", "website": "https://smartct.tuwien.ac.at/", "status": "active", "short_abstract": "

The Research Cluster \"Smart Communities and Technologies\" (Smart CT) at TU Wien will provide the scientific underpinnings for next-generation complex smart city and communities infrastructures. Cities are ever-evolving, complex cyber physical systems of systems covering a magnitude of different areas. The initial concept of smart cities and communities started with cities utilizing communication technologies to deliver services to their citizens and evolved to using information technology to be smarter and more efficient about the utilization of their resources. In recent years however, information technology has changed significantly, and with it the resources and areas addressable by a smart city have broadened considerably. They now cover areas like smart buildings, smart products and production, smart traffic systems and roads, autonomous driving, smart grids for managing energy hubs and electric car utilization or urban environmental systems research.

\r\n\r\n

3D spatialization creates the link between the internet of cities infrastructure and the actual 3D world in which a city is embedded in order to perform advanced computation and visualization tasks. Sensors, actuators and users are embedded in a complex 3D environment that is constantly changing. Acquiring, modeling and visualizing this dynamic 3D environment are the challenges we need to face using methods from Visual Computing and Computer Graphics. 3D Spatialization aims to make a city aware of its 3D environment, allowing it to perform spatial reasoning to solve problems like visibility, accessibility, lighting, and energy efficiency.

\r\n", "abstract": "

The Research Cluster \"Smart Communities and Technologies\" (Smart CT) at TU Wien will provide the scientific underpinnings for next-generation complex smart city and communities infrastructures. Cities are ever-evolving, complex cyber physical systems of systems covering a magnitude of different areas. The initial concept of smart cities and communities started with cities utilizing communication technologies to deliver services to their citizens and evolved to using information technology to be smarter and more efficient about the utilization of their resources. In recent years however, information technology has changed significantly, and with it the resources and areas addressable by a smart city have broadened considerably. They now cover areas like smart buildings, smart products and production, smart traffic systems and roads, autonomous driving, smart grids for managing energy hubs and electric car utilization or urban environmental systems research.

\r\n\r\n

3D spatialization creates the link between the internet of cities infrastructure and the actual 3D world in which a city is embedded in order to perform advanced computation and visualization tasks. Sensors, actuators and users are embedded in a complex 3D environment that is constantly changing. Acquiring, modeling and visualizing this dynamic 3D environment are the challenges we need to face using methods from Visual Computing and Computer Graphics. 3D Spatialization aims to make a city aware of its 3D environment, allowing it to perform spatial reasoning to solve problems like visibility, accessibility, lighting, and energy efficiency.

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It allows observing realistic representations in a three-dimensional virtual space as it is used in games and simulations of specific situations. One way to achieve this is procedural modeling, a method that only needs little input to generate complex scenes and structures. In combination with so-called parser generators, an efficient and less time-consuming approach is achieved. The resulting application then gives the user a simple and fast way to generate, model, and design highly complex structures. In this thesis, we first will go into detail about today’s standards and the possibilities which are available at the moment. Then resume with an illustration of two widely used parser generators called ANTLR and Bison and how we replaced the first with the second. Leaving us with a comparison, of their advantages and disadvantages and demonstrating the resulting outcome.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1193, "image_height": 1045, "name": "gamsjaeger-2022-proc-teaser.png", "type": "image/png", "size": 551042, "path": "Publication:gamsjaeger-2022-proc", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/gamsjaeger-2022-proc/gamsjaeger-2022-proc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/gamsjaeger-2022-proc/gamsjaeger-2022-proc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1924, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Alexandra", "lastname": "Gamsjäger", "searchname": "Alexandra Gamsjäger", 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