[ { "id": "Pahr2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16617", "title": "Vologram: Educational Craftworks for Volume Physicalization", "date": "2020-22-24", "abstract": "Long before the onset of computer technology, anatomical sculptures were already used for educational purposes. Digital imaging technology and its incorporation into the clinical workflow through the advancements of medical visualization led to a steady decline in the use of sculpture-based teaching aids. Currently, anatomical volume visualizations are predominantly presented on computer screens. Recent developments in augmented, mixed, and virtual reality o˙er new, exciting ways to digitally display medical imaging data. In recent years, the application of real-world sculptures to display patient imaging data has seen a resurgence through the field of data physicalization. Predominantly, it has been used to enhance the education of medical personnel and laymen through the use of physical models. Expensive 3D printing technology is often employed in the creation of high fidelity anatomical sculptures, with realistic look-and-feel. However, few approaches make use of a˙ordable physicalizations in the field of layman anatomical education.\nIn the course of this thesis di˙erent ways to introduce self-made, custom physical-izations into layman medical education are explored. We propose a suitable concept, the Vologram, to display medical volume data in a visually appealing way for medical non-experts. This takes the form of slide-based sculptures, made out of a˙ordable ma-terials available to the general public with a high degree of interactivity, and can be produced through commonly available means. To support a customizable workflow in the creation of these sculptures, we provide a stand-alone desktop application, which allows layman users to create custom educational sculptures. Real medical imaging data can be filtered and displayed in di˙erent ways, delivering optically diverse results. We evaluate the concept in a small scale study, to determine the e˙ect of interactive medical visualizations as opposed to physicalizations on the target audience. The results of this study point to a great potential for the application of interactive educational concepts for layman anatomical education.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 228, "image_height": 213, "name": "Pahr2020-Image.JPG", "type": "image/jpeg", "size": 15174, "path": "Publication:Pahr2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1813 ], "co_supervisor": [ 1464 ], "date_end": "2020-11-24", "date_start": "2020-01-12", "diploma_examina": "2020-11-29", "doi": "10.34726/hss.2021.79540", "matrikelnr": "0906438", "open_access": "yes", "pages": "131", "supervisor": [ 166 ], "research_areas": [ "Modeling" ], "keywords": [ "Phyiscalizations", "Anatomy Education" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 228, "image_height": 213, "name": "Pahr2020-Image.JPG", "type": "image/jpeg", "size": 15174, "path": "Publication:Pahr2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Pahr2020-Master Thesis.pdf", "type": "application/pdf", "size": 4742026, "path": "Publication:Pahr2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Pahr2020-Poster.pdf", "type": "application/pdf", "size": 4546791, "path": "Publication:Pahr2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/Pahr2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pahr2020/", "__class": "Publication" }, { "id": "Ortner_PhD", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/18026", "title": "Tight Integration of Visual Analysis and 3D Real-Time Rendering", "date": "2020-12-29", "abstract": "In many domains, such as urban planning, civil engineering, or disaster management, analysts\nneed to deal with complex geometric data that also contain multivariate attributes. In addition to\nthe visual analysis of the attribute data, typical tasks involve the localization and understanding\nof shapes, and judging spatial relations between geometric objects and the surrounding geometry,\nas for instance a digital terrain model. One way to address this in a visualization design is with\ncoordinated multiple views, combining a 3D geometric view and attribute views by brushing\n& linking. However, a naive coordination of such views highlights challenges inherent to 3D\nvisualization, as brushed objects may be occluded or lie outside of the current viewing volume.\nThis can easily lead to disorientation and failing of localization, shape understanding, and spatial\nrelation tasks, which ultimately breaks the iterative analysis loop provided through coordinated\nmultiple views.\nIn this thesis we explore different visual integration approaches for combining geometric and\nattribute views with respect to three application domains. In the first chapter, we deal with the\ndomain of tunnel inspection and documentation, concerned with revealing patterns in tunnel\ncrack data. We integrate a 3D geometric view with multiple attribute views to a coordinated\nmultiple view solution and present several domain-specific visualization and interaction strategies\nto overcome the aforementioned challenges. We conclude the chapter with a methodological\nframework that provides visualization designers with integration guidelines regarding ‘Guided\nNavigation’, ‘Enhanced Geometric Rendering’, and ‘Similarity-based Analysis’.\nIn the second chapter, we explore the potential visual impact of candidate buildings to a cityscape\nin the context of visibility-aware urban planning. We present the visualization system Vis-A-Ware\nto qualitatively and quantitatively evaluate and compare visibility data of candidate buildings\nwith respect to a large number of viewpoints. Vis-A-Ware features a 3D view of an urban scene\nand a novel ranking view to compare and filter candidates with respect to visual impact data\nderived from visibility evaluations. The ranking view is tightly integrated with the other views\nfor qualitative evaluation and to judge spatial relations in the cityscape. We provide users with a\nworkflow to ultimately arrive at a small set of candidates supporting a jury-based decision-making\nprocess.\nIn the third chapter, we are concerned with the domain of geological analysis of digital outcrop\nmodels (DOMs) which plays an essential role in the current NASA and ESA missions seeking\nsigns of past life on Mars. Geologists interpret and measure DOMs, create sedimentary logs, and\ncombine them in ‘correlation panels’. Currently, the creation of correlation panels is manual and therefore time-consuming, and inflexible. With InCorr we present a visualization solution that\nencompasses a 3D logging tool and an interactive data-driven correlation panel that evolves with\nthe stratigraphic analysis. Correlation panels are an important part of geological publications.\nWith InCorr we provide geologists with an interactive correlation panel that is reproducible and\ntakes significantly less effort to create.\nThe results of this thesis demonstrate that the tight integration of 3D geometric and attribute\nviews is essential for certain domains and needs to be approached in a methodological way with\nthoughtful visualization and interaction design.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 510, "image_height": 341, "name": "Ortner_PhD-image.JPG", "type": "image/jpeg", "size": 47751, "path": "Publication:Ortner_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1277 ], "doi": "10.34726/hss.2021.92046", "duration": "4", "matrikelnr": "00928153", "open_access": "yes", "pages": "116", "reviewer_1": [ 1690 ], "reviewer_2": [ 1248 ], "rigorosum": "2021-03-12", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [ "Interactive Visualization", "Integration Spatial and Non-Spatial Data Visualization", "Methodology" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 510, "image_height": 341, "name": "Ortner_PhD-image.JPG", "type": "image/jpeg", "size": 47751, "path": "Publication:Ortner_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-image:thumb{{size}}.png" }, { "description": null, "filetitle": "PhD thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Ortner_PhD-PhD thesis.pdf", "type": "application/pdf", "size": 59685331, "path": "Publication:Ortner_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-PhD thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/Ortner_PhD-PhD thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner_PhD/", "__class": "Publication" }, { "id": "AA2020", "type_id": "xmascard", "tu_id": null, "repositum_id": null, "title": "X-Mas Card 2020", "date": "2020-12-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Cover", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1755, "image_height": 2481, "name": "AA2020-Cover.jpg", "type": "image/jpeg", "size": 433045, "path": "Publication:AA2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Cover:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1170 ], "research_areas": [ "Modeling" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Card", "main_file": true, "use_in_gallery": true, "access": "public", "name": "AA2020-Card.pdf", "type": "application/pdf", "size": 8130125, "path": "Publication:AA2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Card.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Card:thumb{{size}}.png" }, { "description": null, "filetitle": "Cover", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1755, "image_height": 2481, "name": "AA2020-Cover.jpg", "type": "image/jpeg", "size": 433045, "path": "Publication:AA2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/AA2020-Cover:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/AA2020/", "__class": "Publication" }, { "id": "luidolt-2020-lightperceptionVR", "type_id": "journalpaper", "tu_id": 291224, "repositum_id": "20.500.12708/140951", "title": "Gaze-Dependent Simulation of Light Perception in Virtual Reality", "date": "2020-12", "abstract": "The perception of light is inherently different inside a virtual reality (VR) or augmented reality (AR) simulation when compared to the real world. Conventional head-worn displays (HWDs) are not able to display the same high dynamic range of brightness and color as the human eye can perceive in the real world. To mimic the perception of real-world scenes in virtual scenes, it is crucial to reproduce the effects of incident light on the human visual system. In order to advance virtual simulations towards perceptual realism, we present an eye-tracked VR/AR simulation comprising effects for gaze-dependent temporal eye adaption, perceptual glare, visual acuity reduction, and scotopic color vision. Our simulation is based on medical expert knowledge and medical studies of the healthy human eye. We conducted the first user study comparing the perception of light in a real-world low-light scene to a VR simulation. Our results show that the proposed combination of simulated visual effects is well received by users and also indicate that an individual adaptation is necessary, because perception of light is highly subjective.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1478, "image_height": 534, "name": "luidolt-2020-lightperceptionVR-image.jpg", "type": "image/jpeg", "size": 1390298, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1577, 193, 1030 ], "cfp": { "name": "Screenshot_2020-10-30 Call for Papers – ISMAR 2020 – International Symposium on Mixed and Augmented Reality.png", "type": "image/png", "error": "0", "size": "219516", "orig_name": "Screenshot_2020-10-30 Call for Papers – ISMAR 2020 – International Symposium on Mixed and Augmented Reality.png", "ext": "png" }, "date_from": "2020-11-09", "date_to": "2020-11-13", "doi": "10.1109/TVCG.2020.3023604", "event": "ISMAR 2020​", "first_published": "2020-09-17", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1577 ], "location": "online", "pages_from": "3557", "pages_to": "3567", "volume": "Volume 26, Issue 12", "research_areas": [ "Perception", "Rendering", "VR" ], "keywords": [ "perception", "virtual reality", "user studies" ], "weblinks": [ { "href": "https://youtu.be/cY6z2pD7dWc", "caption": "Conference Talk", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "additional-material", "main_file": false, "use_in_gallery": false, "access": "public", "name": "luidolt-2020-lightperceptionVR-additional-material.pdf", "type": "application/pdf", "size": 37540896, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-additional-material.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-additional-material:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1478, "image_height": 534, "name": "luidolt-2020-lightperceptionVR-image.jpg", "type": "image/jpeg", "size": 1390298, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "luidolt-2020-lightperceptionVR-paper.pdf", "type": "application/pdf", "size": 31511229, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "slides", "main_file": false, "use_in_gallery": false, "access": "public", "name": "luidolt-2020-lightperceptionVR-slides.pdf", "type": "application/pdf", "size": 2661389, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-slides:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "luidolt-2020-lightperceptionVR-video.mp4", "type": "video/mp4", "size": 30909955, "path": "Publication:luidolt-2020-lightperceptionVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/luidolt-2020-lightperceptionVR-video:video.mp4" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luidolt-2020-lightperceptionVR/", "__class": "Publication" }, { "id": "sakr_sherif-2020-cacm", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "The Future is Big Graphs! A Community View on Graph Processing Systems", "date": "2020-12", "abstract": "Graphs are by nature ‘unifying abstractions’ that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?\nWe are witnessing an unprecedented growth of interconnected data, which underscores the vital role of graph processing in our society. To name only a few remarkable examples of late, the importance of this field for practitioners is evidenced by the large number (over 50,000) of people registered2 to download the Neo4j book “​Graph Algorithms​” in just over 1.5 years, and by the enormous interest in the use of graph processing in the Artificial Intelligence and Machine Learning fields3. Furthermore, the timely Graphs4Covid-19 initiative4 provides evidence for the importance of big graph analytics in alleviating the global COVID-19 pandemic.\nThis article addresses the questions: How do the next-decade big graph processing systems look like from the perspectives of the data management and the large scale systems communities5? What can we say today about the guiding design principles of these systems in the next 10 years?", "authors_et_al": true, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "sakr_sherif-2020-cacm-image.png", "type": "image/png", "size": 43693, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1805, 1806, 1807, 1808, 1464 ], "journal": "Communications of the ACM ", "pages_from": "1", "pages_to": "14", "volume": "x", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "sakr_sherif-2020-cacm-image.png", "type": "image/png", "size": 43693, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sakr_sherif-2020-cacm-paper.pdf", "type": "application/pdf", "size": 711422, "path": "Publication:sakr_sherif-2020-cacm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/sakr_sherif-2020-cacm-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/sakr_sherif-2020-cacm/", "__class": "Publication" }, { "id": "spegel-gruenberger-2020", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Charakterisierung der Population von Pflegepatienten in zwei Pflegespitälern mithilfe interaktiver Visualisierungen elektronischer Patientendaten", "date": "2020-12", "abstract": "Results only accessible for members of the research unit. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1814 ], "date_end": "2020-12", "date_start": "2020-09", "matrikelnr": "08726501", "note": "194.047 Interdisciplinary Project in Data Science", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/spegel-gruenberger-2020/", "__class": "Publication" }, { "id": "Mossel_Annette_2020-TVR", "type_id": "journalpaper_notalk", "tu_id": 294049, "repositum_id": "20.500.12708/141658", "title": "Immersive training of first responder squad leaders in untethered virtual reality", "date": "2020-12", "abstract": "We present the VROnSite platform that supports immersive training of first responder units´ on-site squad leaders. Our training platform is fully immersive, entirely untethered to ease use and provides two means of navigation-abstract and natural walking-to simulate stress and exhaustion, two important factors for decision making. With the platform´s capabilities, we close a gap in prior art for first responder training. Our research is closely interlocked with stakeholders from multiple fire brigades to gather early feedback in an iterative design process. In this paper, we present the system´s design rationale, provide insight into the process of training scenario development and present results of a user study with 41 squad leaders from the firefighting domain. Virtual disaster environments with two different navigation types were evaluated using quantitative and qualitative measures. Participants considered our platform highly suitable for training of decision making in complex first responder scenarios and results show the importance of the provided navigation technologies in this context.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1815, 1731, 1816, 1727, 1726, 378 ], "doi": "10.1007/s10055-020-00487-x", "journal": "Virtual Reality", "pages_from": "1", "pages_to": "15", "volume": "204", "research_areas": [], "keywords": [ "Virtual Reality", "Mixed Reality", "Augmented Virtuality", "Training", "First Responder", "Interaction", "3D Object Interaction" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mossel_Annette_2020-TVR/", "__class": "Publication" }, { "id": "KROESL-2020-SVI", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/16475", "title": "Simulating Vision Impairments in Virtual and Augmented Reality", "date": "2020-11-30", "abstract": "There are at least 2.2 billion people affected by vision impairments worldwide, and the number of people suffering from common eye diseases like cataracts, diabetic retinopathy, glaucoma or macular degeneration, which show a higher prevalence with age, is expected to rise in the years to come, due to factors like aging of the population.\n\nMedical publications, ophthalmologists and patients can give some insight into the effects of vision impairments, but for people with normal eyesight (even medical personnel) it is often hard to grasp how certain eye diseases can affect perception. We need to understand and quantify the effects of vision impairments on perception, to design cities, buildings, or lighting systems that are accessible for people with vision impairments. Conducting studies on vision impairments in the real world is challenging, because it requires a large number of participants with exactly the same type of impairment. Such a sample group is often hard or even impossible to find, since not every symptom can be assessed precisely and the same eye disease can be experienced very differently between affected people.\n\nIn this thesis, we address these issues by presenting a system and a methodology to simulate vision impairments, such as refractive errors, cataracts, cornea disease, and age-related macular degeneration in virtual reality (VR) and augmented reality (AR), which allows us to conduct user studies in VR or AR with people with healthy eyesight and graphically simulated vision impairments. We present a calibration technique that allows us to calibrate individual simulated symptoms to the same level of severity for every user, taking hardware constraints as well as vision capabilities of users into account.\n\nWe measured the influence of simulated reduced visual acuity on maximum recognition distances of signage in a VR study and showed that current international standards and norms do not sufficiently consider people with vision impairments. In a second study, featuring our medically based cataract simulations in VR, we found that different lighting systems can positively or negatively affect the perception of people with cataracts. We improved and extended our cataract simulation to video–see-through AR and evaluated and adjusted each simulated symptom together with cataract patients in a pilot study, showing the flexibility and potential of our approach. In future work we plan to include further vision impairments and open source our software, so it can be used for architects and lighting designers to test their designs for accessibility, for training of medical personnel, and to increase empathy for people with vision impairments. This way, we hope to contribute to making this world more inclusive for everyone.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 539, "image_height": 270, "name": "KROESL-2020-SVI-image.jpg", "type": "image/jpeg", "size": 32618, "path": "Publication:KROESL-2020-SVI", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1030 ], "co_supervisor": [ 1559 ], "date_end": "2020-10", "date_start": "2016-04", "duration": "4.5 years", "open_access": "yes", "reviewer_1": [ 1299 ], "reviewer_2": [ 1299 ], "rigorosum": "2020-11-30", "supervisor": [ 193 ], "research_areas": [ "Rendering", "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 539, "image_height": 270, "name": "KROESL-2020-SVI-image.jpg", "type": "image/jpeg", "size": 32618, "path": "Publication:KROESL-2020-SVI", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "KROESL-2020-SVI-thesis.pdf", "type": "application/pdf", "size": 7596645, "path": "Publication:KROESL-2020-SVI", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/KROESL-2020-SVI-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/KROESL-2020-SVI/", "__class": "Publication" }, { "id": "Brandstaetter2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16613", "title": "Building a Sandbox Towards Investigating the Behavior of Control Algorithms and Training of Real-World Robots", "date": "2020-11-26", "abstract": "The control of legged robots and teaching robotic hands to grasp are still challenging tasks. Machine learning approaches already work well in simulation. However, the discrepancy between simulation and reality sometimes causes diÿculties when applying simulation results to the real robot. Learning algorithms also require a huge amount of training data. The goal of this work is to build a sandbox that provides a detailed comparison between simulated and real-world robots and o˙ers a way of controlled and continuous data collection and exploration.\nThe sandbox consists of a motion capture and a simulation component. The motion capture component is responsible for the continuous data collection and is realized with a system from OptiTrack with six high-precision infrared cameras. The simulation com-ponent is realized with Simulink and the Simscape Multibody Library. This component is responsible for the exploration and comparison of simulated data with real-world data. The robot that is selected for this work is a small four-legged puppy robot from ROBOTIS that is actuated with 15 Dynamixel servomotors. To integrate the robot into the sandbox, the robot’s controller is reprogrammed to make a transfer from motion data to the robot easier and to control the robot remotely. The robot is programmed with a straight walking gait and equipped with reflective markers to track its movements.\nWith the computer-aided design (CAD) software SolidWorks, a 3D model of the puppy robot is constructed that is used for simulation in Simulink.\nThe result is a system that accurately gathers 6 degrees of freedom (DOF) data of a small robot. This data is transferred to the simulation and can be compared to simulated data. Data from the simulation can also be tested easily on the real robot and tracked again. This way, a closed-loop system is provided for iterative robot exploration.\nTwo datasets are compared with the help of the resulting sandbox: A dataset from ROBOTIS containing ideal joint angles for the robot, and a dataset that is obtained with the motion capture system, containing tracked joint angles. The datasets are simulated and the position and orientation of the robot are compared to the data from the motion capture. Despite strong variations in the simulated results, the simulated robot kept a similar direction and was only a few centimetres o˙ from the real robot.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 382, "image_height": 266, "name": "Brandstaetter2020-Image.JPG", "type": "image/jpeg", "size": 19533, "path": "Publication:Brandstaetter2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1502 ], "date_end": "2020-11-26", "date_start": "2020-10-20", "diploma_examina": "2020-11-26", "doi": "10.34726/hss.2021.69348", "matrikelnr": "01326465", "open_access": "yes", "pages": "108", "supervisor": [ 166 ], "research_areas": [ "Modeling" ], "keywords": [ "robotic motion analysis", "visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 382, "image_height": 266, "name": "Brandstaetter2020-Image.JPG", "type": "image/jpeg", "size": 19533, "path": "Publication:Brandstaetter2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Brandstaetter2020-Master Thesis.pdf", "type": "application/pdf", "size": 20202554, "path": "Publication:Brandstaetter2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Brandstaetter2020-Poster.pdf", "type": "application/pdf", "size": 3741067, "path": "Publication:Brandstaetter2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/Brandstaetter2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Brandstaetter2020/", "__class": "Publication" }, { "id": "Ortner2020", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/55606", "title": "InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis", "date": "2020-11-25", "abstract": "Geological analysis of 3D Digital Outcrop Models (DOMs) for reconstruction of ancient habitable environments is a key aspect of the upcoming ESA ExoMars 2022 Rosalind Franklin Rover and the NASA 2020 Rover Perseverance missions in seeking signs of past life on Mars. Geologists measure and interpret 3D DOMs, create sedimentary logs and combine them in ‘correlation panels’ to map the extents of key geological horizons, and build a stratigraphic model to understand their position in the ancient landscape. Currently, the creation of correlation panels is completely manual and therefore time-consuming, and inflexible. With InCorr we present a visualization solution that encompasses a 3D logging tool and an interactive data-driven correlation panel that evolves with the stratigraphic analysis. For the creation of InCorr we closely cooperated with leading planetary geologists in the form of a design study. We verify our results by recreating an existing correlation analysis with InCorr and validate our correlation panel against a manually created illustration. Further, we conducted a user-study with a wider circle of geologists. Our evaluation shows that InCorr efficiently supports the domain experts in tackling their research questions and that it has the potential to significantly impact how geologists work with digital outcrop representations in general.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 453, "image_height": 323, "name": "Ortner2020-Image.JPG", "type": "image/jpeg", "size": 47209, "path": "Publication:Ortner2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1277, 1494, 1817, 1818, 1819, 166 ], "cfp": { "name": "Papers - Call For Participation VAST 2020.pdf", "type": "application/pdf", "error": "0", "size": "797195", "orig_name": "Papers - Call For Participation VAST 2020.pdf", "ext": "pdf" }, "date_from": "2020-10", "date_to": "2020-10", "doi": "10.1109/TVCG.2020.3030409", "event": "VAST 2020: IEEE Symposium on Visual Analytics Science and Technology", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1277 ], "open_access": "yes", "pages_from": "1", "pages_to": "10", "volume": "21", "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 453, "image_height": 323, "name": "Ortner2020-Image.JPG", "type": "image/jpeg", "size": 47209, "path": "Publication:Ortner2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Ortner2020-Paper.pdf", "type": "application/pdf", "size": 16071836, "path": "Publication:Ortner2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/Ortner2020-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Ortner2020/", "__class": "Publication" }, { "id": "Gogel2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16605", "title": "Visualization-Guided Classification of Carbonized Seeds from Early Human Civilizations", "date": "2020-11-25", "abstract": "Since the Neolithic Revolution approximately 10.000 years ago, crop plants are an important part of our food. Researchers of archeobotany try to find and determine the species that humankind used already in the past. Most of the gathered samples are preserved due to carbonization, but the shape and inner structures are deformed because of this process. The amount of distortion is given by the temperature and the time they are heated. Normally, an expert is consulted to classify them. Since there are only a few experts in this field, an automatic approach is requested. The result of this work is a software, which can load the Computed Tomography (CT) scans, segment and separate the seeds within the samples, calculate different shape features as descriptors, and train a classifier. To have an overview of how the seeds look like, different volume visualizations are available to show selected samples or median seeds of each class. To validate the probabilities of the learner, additional visualizations are available, which show the influence of the extracted features on the classification. A cross validation method with 1043 known samples results in a classification accuracy of 85 %. The incorrectly classified samples of the ground truth are visualized to display the expert user where they are located regard to the extracted features and which results are especially inaccurate. It turned out, that the opportunity to export the features into a tabular filetype and the visualization of the output probabilities of the classifier for each species were particularly helpful for the domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 638, "image_height": 331, "name": "Gogel2020-Image.JPG", "type": "image/jpeg", "size": 29779, "path": "Publication:Gogel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1617 ], "co_supervisor": [ 1110 ], "date_end": "2020-11-25", "date_start": "2020-01-12", "diploma_examina": "2020-12-15", "doi": "10.34726/hss.2021.62641", "matrikelnr": "0801243", "open_access": "yes", "pages": "105", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [ "Visualization-Guided Classification", "Ancient Seeds" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 638, "image_height": 331, "name": "Gogel2020-Image.JPG", "type": "image/jpeg", "size": 29779, "path": "Publication:Gogel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Gogel2020-Master Thesis.pdf", "type": "application/pdf", "size": 11583640, "path": "Publication:Gogel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Gogel2020-Poster.pdf", "type": "application/pdf", "size": 3402234, "path": "Publication:Gogel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/Gogel2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gogel2020/", "__class": "Publication" }, { "id": "Heim_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16606", "title": "Visual Comparison of Multivariate Data Ensembles", "date": "2020-11-24", "abstract": "In safety-critical areas such as aeronautics, but also in other sectors such as the leisure industry, the advancement of respective products is largely driven by the improvement of the materials used. In order to analyze the targeted properties of these new materials, data of the internal structures is generated, using imaging techniques such as X-ray computed tomography (XCT), which is then analyzed in detail using segmentation and quantification algorithms. For materials scientists, the exact design of the internal structures is crucial for the characterization of materials and a comparison of several material candidates based on their characteristics is therefore indispensable for the investigation of di˙erent manufacturing and optimization processes or property behavior.\nCurrently, material scientists are dependent on sequential comparisons when analyzing several material candidates. Distributions of the individual attributes across the material systems need to be compared, which is why this task is typically cognitively demanding, time consuming, and thus error-prone. This work aims to support domain experts in their daily tasks of analysing large ensembles of material data. For this purpose we developed a comparative visualization framework that provides a holistic picture of similarities and dissimilarities in the data by means of an overview visualization and three detailed visualization techniques. Using the dimension reduction method Multidimensional Scaling, the individual structures are summarized and rendered in a table-based visualization technique called Histogram-Table. Information, describing in which attributes the structures are most similar as well as their exact characteristics, is evaluated by statistical calculations, the results of which are visualized in a bar chart and box plot. Finally, the linear correlations between the individual characteristics can be explored in a correlation map. We present the usability of this visualization system by means of three concrete usage scenarios and verify its applicability by means of a qualitative study with 12 material experts. The knowledge gained from our work represents a significant step in the field of comparative material analysis of high-dimensional data and supports experts in making their work easier and more eÿcient.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 262, "image_height": 520, "name": "Heim_2020-Image.JPG", "type": "image/jpeg", "size": 29877, "path": "Publication:Heim_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1354 ], "co_supervisor": [ 611 ], "date_end": "2020-11-24", "date_start": "2020-01-12", "diploma_examina": "2020-11-24", "matrikelnr": "01226809", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 262, "image_height": 520, "name": "Heim_2020-Image.JPG", "type": "image/jpeg", "size": 29877, "path": "Publication:Heim_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Heim_2020-Master Thesis.pdf", "type": "application/pdf", "size": 20005273, "path": "Publication:Heim_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Heim_2020-Poster.pdf", "type": "application/pdf", "size": 889017, "path": "Publication:Heim_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/Heim_2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Heim_2020/", "__class": "Publication" }, { "id": "Gall2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16616", "title": "Immersive Analytics of Multidimensional Volumetric Data", "date": "2020-11-24", "abstract": "Understanding and interpreting volumetric multidimensional data is a complex and cognitively demanding task. Especially in the field of material science the exploration of large spatial data is crucial. Non-destructive testing (NDT) plays an essential role in industrial production, especially in the field of material and component testing, regarding the analysis, visualization, and optimization of new, highly complex material systems such as fiber composites. In order to support the increasing demands on these materials and components of the future in industrial applications, extensive inspections and controls are essential. NDT inspection data generated by imaging techniques such as X-ray computed tomography (XCT) include 2D images, volumetric models, and derived high-dimensional data spaces. They can rarely, or only to a limited extent, be evaluated on desktop monitors using standard 2D visualization techniques. Therefore, novel immersive visualization and interaction techniques using Virtual Reality (VR) were developed in this thesis to investigate highly complex, heterogeneous material systems. We present a novel technique called \"Model in Miniature\" for an effective and interactive exploration and visual analysis of fiber characteristics. Furthermore, we combine different approaches like exploded views, histograms, and node-link diagrams to provide unique insights into the composite materials. Using embodied interaction and navigation, and enhancing the user’s abilities, previously impossible insights into the most complex material structures are possible. We use the latest findings from the field of Immersive Analytics to make the spatial data more comprehensible and test the results in a qualitative study with domain experts. The evaluation of our techniques has shown positive results, which indicate the benefits of an immersive analysis of composite materials and the exploration of overall high-dimensional volumes. The insights gained therefore represent an important step towards the further development of future immersive analysis platforms.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 502, "image_height": 298, "name": "Gall2020-Image.JPG", "type": "image/jpeg", "size": 31463, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1355 ], "co_supervisor": [ 611 ], "date_end": "2020-11-24", "date_start": "2020-01-15", "diploma_examina": "2020-11-24", "matrikelnr": "01225540", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 502, "image_height": 298, "name": "Gall2020-Image.JPG", "type": "image/jpeg", "size": 31463, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Gall2020-Master Thesis.pdf", "type": "application/pdf", "size": 17524989, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Gall2020-Poster.pdf", "type": "application/pdf", "size": 2277755, "path": "Publication:Gall2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/Gall2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Gall2020/", "__class": "Publication" }, { "id": "Antonini2020", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141814", "title": "Spinel web: an interactive web application for visualizing the chemical composition of spinel group minerals", "date": "2020-11-23", "abstract": "The spinel group minerals provide useful information regarding the geological environment in which the host rocks were formed, constituting excellent petrogenetic indicators, and guides in the search for mineral deposits of economic interest. In this article, we present the Spinel Web, a web application to visualize the chemical composition of spinel group minerals. Spinel Web integrates most of the diagrams commonly used for analyzing the chemical characteristics of the spinel group minerals. It incorporates parallel coordinates and a 3D representation of the spinel prisms. It also provides coordinated views and appropriate interactions for users to interact with their datasets. Spinel Web also supports semi-automatic categorization of the geological environment of formation through a standard Web browser.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 300, "image_height": 222, "name": "Antonini2020-Image.JPG", "type": "image/jpeg", "size": 15627, "path": "Publication:Antonini2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1820, 1228, 1229, 1233, 235, 166, 1232, 1231 ], "doi": "10.1007/s12145-020-00542-w", "first_published": "2020-11-23", "issn": "18650473", "journal": "Earth Science Informatics", "open_access": "yes", "pages_from": "1", "pages_to": "8", "volume": "13", "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 300, "image_height": 222, "name": "Antonini2020-Image.JPG", "type": "image/jpeg", "size": 15627, "path": "Publication:Antonini2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Antonini2020-Paper.pdf", "type": "application/pdf", "size": 1324523, "path": "Publication:Antonini2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/Antonini2020-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Antonini2020/", "__class": "Publication" }, { "id": "Koeppel2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16611", "title": "Context-Responsive Labeling in Augmented Reality", "date": "2020-11-18", "abstract": "Route planning is a common task that often requires additional information on Points-of-Interest (POIs). Augmented Reality (AR) enables mobile users to explore text labels and provides a composite view associated with additional information in a real-world environment. Displaying all labels for Points-of-Interest on a mobile device will lead to unwanted overlaps, and thus a context-responsive strategy to properly arrange labels is expected. This framework should consider removing overlaps, the correct Level-of-Detail to be presented, and also label coherence. This is necessary as the viewing angle in an AR system may change frequently due to users’ behaviors. The consistency of labels plays an essential role in retaining user experience and knowledge, as well as avoiding motion sickness. In this thesis, we aim to develop an approach that systematically manages label visibility and Levels-of-Detail, as well as eliminates unexpected incoherent label movement. To achieve this, we introduce three label management strategies, including (1) Occlusion Management, (2) Level-of-Detail Management, and (3) Coherence Management. A greedy approach is developed for fast occlusion handling. A Level-of-Detail scheme is adopted to arrange various types of labels in AR. A 3D scene manipulation is built to simultaneously suppress the incoherent behaviors induced by the changes of viewing angles. Finally, we present our approach’s feasibility and applicability by demonstrating one synthetic and two real-world scenarios, followed by a qualitative user study.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 342, "image_height": 315, "name": "Koeppel2020-Image.JPG", "type": "image/jpeg", "size": 18157, "path": "Publication:Koeppel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1367 ], "co_supervisor": [ 1464 ], "date_end": "2020-11-18", "date_start": "2020-02-12", "diploma_examina": "2020-11-18", "matrikelnr": "01327052", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 342, "image_height": 315, "name": "Koeppel2020-Image.JPG", "type": "image/jpeg", "size": 18157, "path": "Publication:Koeppel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Koeppel2020-Master Thesis.pdf", "type": "application/pdf", "size": 16776419, "path": "Publication:Koeppel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Koeppel2020-Poster.pdf", "type": "application/pdf", "size": 4132411, "path": "Publication:Koeppel2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/Koeppel2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/", "__class": "Publication" }, { "id": "wu-2020-tvcg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/140950", "title": "Multi-level Area Balancing of Clustered Graphs", "date": "2020-11-17", "abstract": "We present a multi-level area balancing technique for laying out clustered graphs to facilitate a comprehensive understanding of the complex relationships that exist in various fields, such as life sciences and sociology. Clustered graphs are often used to model relationships that are accompanied by attribute-based grouping information. Such information is essential for robust data analysis, such as for the study of biological taxonomies or educational backgrounds. Hence, the ability to smartly arrange textual labels and packing graphs within a certain screen space is therefore desired to successfully convey the attribute data . Here we propose to hierarchically partition the input screen space using Voronoi tessellations in multiple levels of detail. In our method, the position of textual labels is guided by the blending of constrained forces and the forces derived from centroidal Voronoi cells. The proposed algorithm considers three main factors: (1) area balancing, (2) schematized space partitioning, and (3) hairball management. We primarily focus on area balancing, which aims to allocate a uniform area for each textual label in the diagram. We achieve this by first untangling a general graph to a clustered graph through textual label duplication, and then coupling with spanning-tree-like visual integration. We illustrate the feasibility of our approach with examples and then evaluate our method by comparing it with well-known conventional approaches and collecting feedback from domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1579, 171 ], "doi": "https://doi.org/10.1109/TVCG.2020.3038154", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "open_access": "yes", "pages_from": "1", "pages_to": "15", "volume": "x", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [ "Graph drawing", "Voronoi tessellation", "multi-level", "spatially-efficient layout" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 48103600, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-video.mov", "type": "video/quicktime", "size": 12802528, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video.mov", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:video.mp4" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/", "__class": "Publication" }, { "id": "WIMMER-2020-ASG", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Applications of Smart Graphics", "date": "2020-11-12", "abstract": "For a long period of time, the focus of computer graphics was mostly the quality and speed of image generation. Meanwhile, commercial rendering engines leave little to be desired, but computer graphics research has expanded to solve application problems through so-called “smart graphics”. In this talk, I will present some of our latest advances in “smart” computer graphics in simulation, rendering and content generation. I will show how we can now simulate visual impairments in virtual reality, which could be used to create empathy for people affected by these impairments. I will describe how we have advanced point-based rendering techniques to allow incorporating real environments into rendering applications with basically no preprocessing. On the other hand, virtual environments could be created efficiently by collaborative crowed-sourced procedural modeling. Finally, efficient simulations of floods and heavy rainfall may help experts and increase public awareness of natural disasters and the effects of climate change.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 193 ], "date_from": "2020-11-12", "date_to": "2020-11-13", "event": "Smart Tools and Applications in Graphics (STAG) 2020", "location": "online", "open_access": "yes", "research_areas": [ "Modeling", "Rendering" ], "keywords": [ "computer graphics", "rendering", "simulation" ], "weblinks": [], "files": [], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/WIMMER-2020-ASG/", "__class": "Publication" }, { "id": "Groeller_V5_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87185", "title": "Interactive Visual Data Analysis", "date": "2020-11-09", "abstract": "Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analyses, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. The concepts will be especially exemplified with a geospatial decision support system for flood management. Given the amplified data variability, interactive visual data analyses are likely to gain in importance in the future. Research challenges and directions are sketched at the end of the talk.\n", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "date_from": "2020-11-09", "date_to": "2020-11-09", "event": "KAUST CEMSE Graduate Seminar (virtual)", "location": "KAUST, Saudi Arabia", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://cemse.kaust.edu.sa/events/event/interactive-visual-data-analysis", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V5_2020/", "__class": "Publication" }, { "id": "Kroesl_2020_11_09", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/55554", "title": "CatARact: Simulating Cataracts in Augmented Reality", "date": "2020-11-09", "abstract": "For our society to be more inclusive and accessible, the more than 2.2 billion people worldwide with limited vision should be considered more frequently in design decisions, such as architectural planning. To help architects in evaluating their designs and give medical per-sonnel some insight on how patients experience cataracts, we worked with ophthalmologists to develop the first medically-informed, pilot-studied simulation of cataracts in eye-tracked augmented reality (AR). To test our methodology and simulation, we conducted a pilot study with cataract patients between surgeries of their two cataract-affected eyes. Participants compared the vision of their corrected eye, viewing through simulated cataracts, to that of their still affected eye, viewing an unmodified AR view. In addition, we conducted remote experiments via video call, live adjusting our simulation and comparing it to related work, with participants who had cataract surgery a few months before. We present our findings and insights from these experiments and outline avenues for future work.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1024, "image_height": 512, "name": "Kroesl_2020_11_09-image.png", "type": "image/png", "size": 483244, "path": "Publication:Kroesl_2020_11_09", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1030, 1633, 1577, 1636, 1635, 1634, 193 ], "booktitle": "IEEE International Symposium on Mixed and Augmented Reality (ISMAR).", "cfp": { "name": "Call for Papers – ISMAR 2020 – International Symposium on Mixed and Augmented Reality.pdf", "type": "application/pdf", "error": "0", "size": "1595938", "orig_name": "Call for Papers – ISMAR 2020 – International Symposium on Mixed and Augmented Reality.pdf", "ext": "pdf" }, "date_from": "2020-11-09", "date_to": "2020-11-13", "event": "IEEE International Symposium on Mixed and Augmented Reality (ISMAR).", "lecturer": [ 1030 ], "open_access": "yes", "pages_from": "1", "pages_to": "10", "research_areas": [ "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1024, "image_height": 512, "name": "Kroesl_2020_11_09-image.png", "type": "image/png", "size": 483244, "path": "Publication:Kroesl_2020_11_09", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Kroesl_2020_11_09-Paper.pdf", "type": "application/pdf", "size": 1809637, "path": "Publication:Kroesl_2020_11_09", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/Kroesl_2020_11_09-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kroesl_2020_11_09/", "__class": "Publication" }, { "id": "SCHUETZ-2020-MPC", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/58254", "title": "Fast Out-of-Core Octree Generation for Massive Point Clouds", "date": "2020-11", "abstract": "We propose an efficient out-of-core octree generation method for arbitrarily large point clouds. It utilizes a hierarchical counting sort to quickly split the point cloud into small chunks, which are then processed in parallel. Levels of detail are generated by subsampling the full data set bottom up using one of multiple exchangeable sampling strategies. We introduce a fast hierarchical approximate blue-noise strategy and compare it to a uniform random sampling strategy. The throughput, including out-of-core access to disk, generating the octree, and writing the final result to disk, is about an order of magnitude faster than the state of the art, and reaches up to around 6 million points per second for the blue-noise approach and up to around 9 million points per second for the uniform random approach on modern SSDs.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2400, "image_height": 692, "name": "SCHUETZ-2020-MPC-.png", "type": "image/png", "size": 848082, "path": "Publication:SCHUETZ-2020-MPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1116, 948, 193 ], "cfp": { "name": "For Authors - PG2020.pdf", "type": "application/pdf", "error": "0", "size": "909462", "orig_name": "For Authors - PG2020.pdf", "ext": "pdf" }, "date_from": "2021", "date_to": "2021", "doi": "10.1111/cgf.14134", "event": "Pacific Graphics 2020", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1116 ], "location": "Wellington, NZ", "number": "7", "open_access": "yes", "pages": "13", "pages_from": "1", "pages_to": "13", "publisher": "John Wiley & Sons, Inc.", "volume": "39", "research_areas": [ "Rendering" ], "keywords": [ "point clouds", "point-based rendering", "level of detail" ], "weblinks": [ { "href": "https://github.com/potree/PotreeConverter/releases/tag/2.0", "caption": "PotreeConverter 2.0 at github ", "description": "PotreeConverter generates an octree LOD structure for streaming and real-time rendering of massive point clouds. The results can be viewed in web browsers with Potree or as a desktop application with PotreeDesktop.\n\n", "main_file": 0 }, { "href": "https://www.youtube.com/watch?v=g6k-flKWaNI", "caption": "Video", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2400, "image_height": 692, "name": "SCHUETZ-2020-MPC-.png", "type": "image/png", "size": 848082, "path": "Publication:SCHUETZ-2020-MPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "SCHUETZ-2020-MPC-paper.pdf", "type": "application/pdf", "size": 25053214, "path": "Publication:SCHUETZ-2020-MPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/SCHUETZ-2020-MPC-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "Superhumans" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/SCHUETZ-2020-MPC/", "__class": "Publication" }, { "id": "Groeller_V42020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87184", "title": "Medicinae Notitia Visibilis Fac – Quo Vadis?", "date": "2020-10-29", "abstract": "Medical Visualization is a scientific field that takes advantage of human vision and perception to amplify cognition and gain insight in (complex) medical data. The interdisciplinarity and the diversity of stakeholders and their greatly varying expertises and expectations, make it a demanding area with many overlapping, but distinct domains. Collaboration and communication is challenged by: “Die Grenzen meiner Sprache bedeuten die Grenzen meiner Welt“ (Ludwig Wittgenstein). This talk reflects on the feedback from an ad hoc and random sampling of my professional network with comments, e.g., from basic and applied visual and medical computing experts, commercial developers of medical software, clinical researchers and practitioners.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "date_from": "2020-10-29", "date_to": "2020-10-29", "event": "IEEE Vis 2020 Application Spotlight (virtual): Recent Challenges in Medical Visualization", "location": "Salt Lake City, USA", "open_access": "yes", "research_areas": [ "MedVis" ], "keywords": [], "weblinks": [ { "href": "https://virtual.ieeevis.org/session_l-med.html", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V42020/", "__class": "Publication" }, { "id": "Meusburger_2020", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of Spatial Deviations via Geospatial Slicing", "date": "2020-10-28", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 495, "image_height": 229, "name": "Meusburger_2020-Image.JPG", "type": "image/jpeg", "size": 28468, "path": "Publication:Meusburger_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1811 ], "date_end": "2020-10-28", "date_start": "2020-04-12", "matrikelnr": "01526330", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Meusburger_2020-Bachelor thesis.pdf", "type": "application/pdf", "size": 8033013, "path": "Publication:Meusburger_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Bachelor thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 495, "image_height": 229, "name": "Meusburger_2020-Image.JPG", "type": "image/jpeg", "size": 28468, "path": "Publication:Meusburger_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/Meusburger_2020-Image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Meusburger_2020/", "__class": "Publication" }, { "id": "erler-2020-p2s", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/55555", "title": "Points2Surf: Learning Implicit Surfaces from Point Clouds", "date": "2020-10-28", "abstract": "A key step in any scanning-based asset creation workflow is to convert unordered point clouds to a surface. Classical methods (e.g., Poisson reconstruction) start to degrade in the presence of noisy and partial scans. Hence, deep learning based methods have recently been proposed to produce complete surfaces, even from partial scans. However, such data-driven methods struggle to generalize to new shapes with large geometric and topological variations. We present Points2Surf, a novel patch-based learning framework that produces accurate surfaces directly from raw scans without normals.\n\nLearning a prior over a combination of detailed local patches and coarse global information improves generalization performance and reconstruction accuracy.\n\nOur extensive comparison on both synthetic and real data demonstrates a clear advantage of our method over state-of-the-art alternatives on previously unseen classes (on average, Points2Surf brings down reconstruction error by 30% over SPR and by 270%+ over deep learning based SotA methods) at the cost of longer computation times and a slight increase in small-scale topological noise in some cases. \nOur source code, pre-trained model, and dataset are available on: https://github.com/ErlerPhilipp/points2surf\n", "authors_et_al": false, "substitute": null, "main_image": { "description": "We present Points2Surf, a method to reconstruct an accurate implicit surface from a noisy point cloud. Unlike current data-driven surface reconstruction methods like DeepSDF and AtlasNet, it is patch-based, improves detail reconstruction, and unlike Screened Poisson Reconstruction (SPR), a learned prior of low-level patch shapes improves reconstruction accuracy. \nNote the quality of reconstructions, both geometric and topological, against the original surfaces. The ability of Points2Surf to generalize to new shapes makes it the first learning-based approach with significant generalization ability under both geometric and topological variations.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4161, "image_height": 2179, "name": "erler-2020-p2s-teaser.png", "type": "image/png", "size": 4130897, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1395, 627, 948, 193, 1771 ], "address": "Cham", "booktitle": "Computer Vision -- ECCV 2020", "cfp": { "name": "eccv_2020_call_for_papers.pdf", "type": "application/pdf", "error": "0", "size": "255221", "orig_name": "eccv_2020_call_for_papers.pdf", "ext": "pdf" }, "date_from": "2020-08-24", "date_to": "2020-08-27", "doi": "10.1007/978-3-030-58558-7_7", "editor": "Vedaldi, Andrea and Bischof, Horst and Brox, Thomas and Frahm, Jan-Michael", "event": "ECCV 2020", "first_published": "2020-10-28", "isbn": "978-3-030-58558-7", "journal": "Computer Vision – ECCV 2020", "lecturer": [ 1395 ], "location": "Glasgow, UK (online)", "open_access": "yes", "pages": "17", "pages_from": "108", "pages_to": "124", "publisher": "Springer International Publishing", "series": "Lecture Notes in Computer Science", "volume": "12350", "research_areas": [ "Geometry", "Modeling" ], "keywords": [ "surface reconstruction", "implicit surfaces", "point clouds", "patch-based", "local and global", "deep learning", "generalization" ], "weblinks": [ { "href": "https://github.com/ErlerPhilipp/points2surf", "caption": "Github Repo", "description": "Access the source code, pre-trained models and datasets from Github.", "main_file": 0 }, { "href": "https://arxiv.org/abs/2007.10453", "caption": "Arxiv Pre-Print", "description": "Access the paper pre-print on arXiv.", "main_file": 0 }, { "href": "https://link.springer.com/chapter/10.1007%2F978-3-030-58558-7_7", "caption": "Official Publication", "description": "Access the paper Springer Link.", "main_file": 0 } ], "files": [ { "description": "Our normalized ground-truth meshes from the ABC dataset.", "filetitle": "abc_meshes", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-abc_meshes.zip", "type": "application/x-zip-compressed", "size": 726933282, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-abc_meshes.zip", "thumb_image_sizes": [] }, { "description": "Our processed extract from the ABC dataset that can be used to train Points2Surf.", "filetitle": "abc_training", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-abc_training.zip", "type": "application/x-zip-compressed", "size": 1786245314, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-abc_training.zip", "thumb_image_sizes": [] }, { "description": "Our processed extract from the ABC dataset that can be used to replicate the results of Points2Surf.", "filetitle": "abc", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-abc.zip", "type": "application/x-zip-compressed", "size": 138638856, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-abc.zip", "thumb_image_sizes": [] }, { "description": "Our pre-trained models (ablation versions) to reproduce the results.", "filetitle": "ablation_models", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-ablation_models.zip", "type": "application/x-zip-compressed", "size": 242492525, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-ablation_models.zip", "thumb_image_sizes": [] }, { "description": "Our processed Famous dataset that can be used to replicate the results of Points2Surf.", "filetitle": "famous", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-famous.zip", "type": "application/x-zip-compressed", "size": 1525449349, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-famous.zip", "thumb_image_sizes": [] }, { "description": "8 min video for ECCV 2020", "filetitle": "long video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-long video.mp4", "type": "video/mp4", "size": 85439106, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-long video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-long video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-long video:video.mp4" }, { "description": "A new model version with even better results.", "filetitle": "max_model", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-max_model.zip", "type": "application/x-zip-compressed", "size": 20010604, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-max_model.zip", "thumb_image_sizes": [] }, { "description": "Points2Surf paper (Arxiv version)", "filetitle": "points2surf_paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-points2surf_paper.pdf", "type": "application/pdf", "size": 9135835, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-points2surf_paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-points2surf_paper:thumb{{size}}.png" }, { "description": "Our processed real-world dataset that can be used to replicate the results of Points2Surf.", "filetitle": "real_world", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-real_world.zip", "type": "application/x-zip-compressed", "size": 5942947, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-real_world.zip", "thumb_image_sizes": [] }, { "description": "2 min video for ECCV 2020", "filetitle": "short video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-short video.mp4", "type": "video/mp4", "size": 13862480, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-short video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-short video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-short video:video.mp4" }, { "description": "We present Points2Surf, a method to reconstruct an accurate implicit surface from a noisy point cloud. Unlike current data-driven surface reconstruction methods like DeepSDF and AtlasNet, it is patch-based, improves detail reconstruction, and unlike Screened Poisson Reconstruction (SPR), a learned prior of low-level patch shapes improves reconstruction accuracy. \nNote the quality of reconstructions, both geometric and topological, against the original surfaces. The ability of Points2Surf to generalize to new shapes makes it the first learning-based approach with significant generalization ability under both geometric and topological variations.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4161, "image_height": 2179, "name": "erler-2020-p2s-teaser.png", "type": "image/png", "size": 4130897, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-teaser:thumb{{size}}.png" }, { "description": "Our processed extract from the Thingi10k dataset that can be used to replicate the results of Points2Surf.", "filetitle": "thingi10k", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-thingi10k.zip", "type": "application/x-zip-compressed", "size": 940826980, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-thingi10k.zip", "thumb_image_sizes": [] }, { "description": "Our pre-trained model (vanilla version) to reproduce the results.", "filetitle": "vanilla_model", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2020-p2s-vanilla_model.zip", "type": "application/x-zip-compressed", "size": 23009153, "path": "Publication:erler-2020-p2s", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/erler-2020-p2s-vanilla_model.zip", "thumb_image_sizes": [] } ], "projects_workgroups": [ "Superhumans", "MAKE-IT-FAB", "ShapeAcquisition" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/erler-2020-p2s/", "__class": "Publication" }, { "id": "pointner_simon-2020", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Controllable Animation for Information Visualisation", "date": "2020-10-23", "abstract": "Understanding and identifying the alternations between different visualisations are cognitively demanding tasks. Distinct visualisations can lead to a different interpretation of data, thus it is important to understand how visualisations correlate with each other and how the insight to the data gained might vary. An approach to achieve the correlation understanding is to introduce animated transitions between different visualisations that allows to precisely follow changes, pursuing the research in the field of animated transitions. In particular, the focus of this research is on animated transitions between commonly used visualisations like bar, doughnut, pie and radial column charts with the addition of implementing them controllable. A controllable animation allows the user to control the animation with a seek-bar like in a video player. This work proposes and implements two new animated transitions, one animation between bar and pie charts and another one for hierarchical bar charts, both utilising other charts as intermediate steps. Expectations are to further improve the effectiveness and graphical perception of animated transitions. Though, a quantitative user study yielded no significant improvements apart from a little effectiveness gain among elder persons.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1796 ], "date_end": "2020-10-23", "date_start": "2019-02-26", "matrikelnr": "01612401", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "pointner_simon-2020-thesis.pdf", "type": "application/pdf", "size": 2063267, "path": "Publication:pointner_simon-2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/pointner_simon-2020-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/pointner_simon-2020-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pointner_simon-2020/", "__class": "Publication" }, { "id": "purgathofer-2020-nch", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87073", "title": "VR and Visualization in Industry", "date": "2020-10-19", "abstract": "We can argue why VR and AR will become more important:\n- Virtual and Augmented Reality are efficient forms of visualizing content for the human:\n\tthey are immersive, 3 dimensional, interactive, natural, and easy to learn\n- Why did that not happen already? Simply because the technology was not ready, there were too many weaknesses. Now technology is ready!\n- And why is visualization important? Visualization is one fundamental pillar of modern computer science.\n- The human eyes carry 80-90% of all information input, images have the highest bandwidth (you know the saying: a picture is worth a thousand words)\n- And a visual summary of information makes it much easier to identify patterns and trends, \tand to analyze data communication easier and more efficient\n", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 190 ], "event": "World VR Industry Conference Cloud Summit", "location": "Nanchang, China", "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/purgathofer-2020-nch/", "__class": "Publication" }, { "id": "lipp-2019-rtxq3", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16178", "title": "Real-Time Ray Tracing in Quake III", "date": "2020-10-15", "abstract": "This work discusses the extension of the popular Quake III game engine using real-time raytracing.\nIt investigates how ray tracing can be implemented using the most recent graphics card generation by NVIDIA, which offers dedicated hardware support and acceleration via an new API.\nIn addition, strategies will be discussed about how offline ray-tracing algorithms can be transformed to an online real-time context.\n\nIn order to implement ray tracing, Quake III needs to be extended with a Vulkan backend.\nNext, distributed ray tracing is implemented and is used to render the whole game world except for the user interface (UI) elements. The UI will be handled by the rasterizer.\n\nThe performance and efficiency of ray tracing in a game engine using the RTX hardware features is analyzed and discussed.\nThe focus lies on how quality and performance relate to each other, and how far ray tracing can be pushed with still acceptable frame rate of around 30/60 frames per second.\nFurthermore, implementation strategies that improve the quality, performance or both will be discussed.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 834, "image_height": 594, "name": "lipp-2019-rtxq3-image.png", "type": "image/png", "size": 963441, "path": "Publication:lipp-2019-rtxq3", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1525 ], "date_end": "2020-10-15", "date_start": "2019-03-19", "diploma_examina": "2020-11-19", "matrikelnr": "01425235", "supervisor": [ 193, 1128 ], "research_areas": [ "Rendering" ], "keywords": [ "Rendering", "Ray Tracing", "RTX", "Quake III" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 834, "image_height": 594, "name": "lipp-2019-rtxq3-image.png", "type": "image/png", "size": 963441, "path": "Publication:lipp-2019-rtxq3", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "lipp-2019-rtxq3-poster.pdf", "type": "application/pdf", "size": 7028484, "path": "Publication:lipp-2019-rtxq3", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "lipp-2019-rtxq3-thesis.pdf", "type": "application/pdf", "size": 7214480, "path": "Publication:lipp-2019-rtxq3", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/lipp-2019-rtxq3-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/lipp-2019-rtxq3/", "__class": "Publication" }, { "id": "zechmeister2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16181", "title": "Interactive Visualization of Vector Data on Heightfields", "date": "2020-10-13", "abstract": "The accurate visualization of huge amounts of georeferenced vector data on heightfields in real-time is a common problem in the field of geographic information systems (GIS). Vector data usually consist of lines and polygons, which represent objects such as roads, rivers, buildings, and parks. The interactive exploration of these vector entities in large-scale virtual 3D environments and the resulting large zoom range pose an additional performance challenge for their visualization. Ensuring clear visibility of all objects of interest in overview and of their details in close-up views is diÿcult in such large-scale environments.\nIn this thesis, a screen-based visualization method of vector data is proposed, which combines two di˙erent approaches, a static and a dynamic approach, to control the behavior and the visibility of the corresponding vector entities. The vector data can represent real-world objects and to preserve their relative size to the rest of the 3D world, a constant object size is used for the static approach. But, this static behavior can cause vector entities to disappear when zooming out. Since lines are especially a˙ected due to their small width, the dynamic approach scales them according to the current view in order to be clearly visible even from far away.\nThe evaluation results show that both screen-based visualization approaches can be applied in real-world use cases of a geospatial decision support system with large-scale environments and vector data consisting of several millions of vertices and still provide real-time performance. The results also highlight that the proposed screen-based visualization method produces larger render overheads compared with a volume-based visualization, but for large vector data sets, the new method outperforms it.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 447, "image_height": 315, "name": "zechmeister2020-image.JPG", "type": "image/jpeg", "size": 47750, "path": "Publication:zechmeister2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1793 ], "co_supervisor": [ 877 ], "date_end": "2020-10-13", "date_start": "2020-01-20", "diploma_examina": "2020-10-13", "doi": "10.34726/hss.2020.75003", "matrikelnr": "01327455", "open_access": "yes", "pages": "107", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [ "View-dependent Visualization", "Vector Data Rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 447, "image_height": 315, "name": "zechmeister2020-image.JPG", "type": "image/jpeg", "size": 47750, "path": "Publication:zechmeister2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "zechmeister2020-Master Thesis.pdf", "type": "application/pdf", "size": 26225569, "path": "Publication:zechmeister2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "zechmeister2020-Poster.pdf", "type": "application/pdf", "size": 2301383, "path": "Publication:zechmeister2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/zechmeister2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zechmeister2020/", "__class": "Publication" }, { "id": "Mazza_2020", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/140975", "title": "Homomorphic-Encrypted Volume Rendering", "date": "2020-10-13", "abstract": "Computationally demanding tasks are typically calculated in dedicated data centers, and real-time visualizations also follow this trend. Some rendering tasks, however, require the highest level of confidentiality so that no other party, besides the owner, can read or see the sensitive data. Here we present a direct volume rendering approach that performs volume rendering directly on encrypted volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data and rendered image are uninterpretable to the rendering server. Our volume rendering pipeline introduces novel approaches for encrypted-data compositing, interpolation, and opacity modulation, as well as simple transfer function design, where each of these routines maintains the highest level of privacy. We present performance and memory overhead analysis that is associated with our privacy-preserving scheme. Our approach is open and secure by design, as opposed to secure through obscurity. Owners of the data only have to keep their secure key confidential to guarantee the privacy of their volume data and the rendered images. Our work is, to our knowledge, the first privacy-preserving remote volume-rendering approach that does not require that any server involved be trustworthy; even in cases when the server is compromised, no sensitive data will be leaked to a foreign party.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1871, "image_height": 757, "name": "Mazza_2020-image.JPG", "type": "image/jpeg", "size": 151232, "path": "Publication:Mazza_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1035, 616, 171 ], "cfp": { "name": "Papers - IEEE VIS 2020.pdf", "type": "application/pdf", "error": "0", "size": "954206", "orig_name": "Papers - IEEE VIS 2020.pdf", "ext": "pdf" }, "date_from": "2020-01-10", "date_to": "2020-10-13", "doi": "10.1109/TVCG.2020.3030436", "event": "IEEE VIS (SciVis) 2020 conference", "first_published": "2020-10-13", "journal": "IEEE Transactions on Visualization andComputer Graphics", "lecturer": [ 1035 ], "open_access": "yes", "pages_from": "1", "pages_to": "10", "volume": "27", "research_areas": [ "MedVis" ], "keywords": [ "Volume Rendering, Transfer Function, Homomorphic-Encryption, Paillier" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1871, "image_height": 757, "name": "Mazza_2020-image.JPG", "type": "image/jpeg", "size": 151232, "path": "Publication:Mazza_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Mazza_2020-Paper.pdf", "type": "application/pdf", "size": 1728814, "path": "Publication:Mazza_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/", "__class": "Publication" }, { "id": "furmanova_2020", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/140976", "title": "VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy", "date": "2020-10", "abstract": "In radiation therapy (RT) for prostate cancer, changes in patient anatomy during treatment might lead to inadequate tumor coverage and higher irradiation of healthy tissues in the nearby pelvic organs. Exploring and analyzing anatomical variability throughout the course of RT can support the design of more robust treatment strategies, while identifying patients that are prone to radiation-induced toxicity. We present VAPOR, a novel application for the exploration of pelvic organ variability in a cohort of patients, across the entire treatment process. Our application addresses: (i) the global exploration and analysis of anatomical variability in an abstracted tabular view, (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated, and (iii) the correlation of anatomical variability with radiation doses and potential toxicity. The workflow is based on available retrospective cohort data, which include segmentations of the bladder, the prostate, and the rectum through the entire treatment period. VAPOR is applied to four usage scenarios, which were conducted with two medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment adaptation to anatomical changes.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1733, 1366, 1445, 1444, 1568, 1569, 166, 1410 ], "doi": "https://doi.org/10.1016/j.cag.2020.07.001", "journal": "Computer & Graphics", "note": "Special Section on VCBM 2019", "pages_from": "25", "pages_to": "38", "volume": "91", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1186, "preview_image_height": 641, "name": "furmanova_2020-paper.pdf", "type": "application/pdf", "size": 3355311, "path": "Publication:furmanova_2020", "preview_name": "furmanova_2020-paper:preview.PNG", "preview_type": "image/png", "preview_size": 382697, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/furmanova_2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/furmanova_2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/furmanova_2020/", "__class": "Publication" }, { "id": "pernsteinre_jakob_2020_eechc", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Ensuring the Effectiveness of CHC++ in Vulkan", "date": "2020-10", "abstract": "Real-time occlusion culling is a valuable tool to increase the performance of real-time rendering applications by detecting and removing invisible geometry from the rendering pipeline. Through new rendering Application Programming Interface (API) like Vulkan and modern hardware, these culling algorithms can become even more powerful. This thesis tries to ensure and evaluate the performance of Coherent Hierarchical Culling Revisited (CHC++) in this new environment by performing various optimisations to the algorithm. The changes include the batching of consecutive draw-calls and occlusion queries into single GPU-queue submits to reduce the overhead on the CPU and GPU. Additionally, the support for alpha blended transparent objects was added to the algorithm, which allows for correct culling and rendering of these objects. The algorithm performs great in environments with high occlusion and does not degrade in performance in the worst case scenario. But the high performance increase of the original implementation could not be replicated, which is attributed to the difference in rendering APIs and hardware improvements.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1912, "image_height": 1009, "name": "pernsteinre_jakob_2020_eechc-teaser.jpg", "type": "image/jpeg", "size": 348241, "path": "Publication:pernsteinre_jakob_2020_eechc", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1795 ], "date_end": "2020-10", "date_start": "2019-10", "matrikelnr": "01627767", "supervisor": [ 193, 1650 ], "research_areas": [ "Rendering" ], "keywords": [ "culling", "real-time", "GPU" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1912, "image_height": 1009, "name": "pernsteinre_jakob_2020_eechc-teaser.jpg", "type": "image/jpeg", "size": 348241, "path": "Publication:pernsteinre_jakob_2020_eechc", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pernsteinre_jakob_2020_eechc-Thesis.pdf", "type": "application/pdf", "size": 2552714, "path": "Publication:pernsteinre_jakob_2020_eechc", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/pernsteinre_jakob_2020_eechc-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/pernsteinre_jakob_2020_eechc/", "__class": "Publication" }, { "id": "raidou_slicedice", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/140980", "title": "Slice and Dice: A PhysicalizationWorkflow for Anatomical Edutainment", "date": "2020-10", "abstract": "During the last decades, anatomy has become an interesting topic in education—even for laymen or schoolchildren. As medical imaging techniques become increasingly sophisticated, virtual anatomical education applications have emerged. Still, anatomical models are often preferred, as they facilitate 3D localization of anatomical structures. Recently, data physicalizations (i.e., physical visualizations) have proven to be effective and engaging—sometimes, even more than their virtual counterparts. So far, medical data physicalizations involve mainly 3D printing, which is still expensive and cumbersome. We investigate alternative forms of physicalizations, which use readily available technologies (home printers) and inexpensive materials (paper or semi-transparent films) to generate crafts for anatomical edutainment. To the best of our knowledge, this is the first computer-generated crafting approach within an anatomical edutainment context. Our approach follows a cost-effective, simple, and easy-to-employ workflow, resulting in assemblable data sculptures (i.e., semi-transparent sliceforms). It primarily supports volumetric data (such as CT or MRI), but mesh data can also be imported. An octree slices the imported volume and an optimization step simplifies the slice configuration, proposing the optimal order for easy assembly. A packing algorithm places the resulting slices with their labels, annotations, and assembly instructions on a paper or transparent film of user-selected size, to be printed, assembled into a sliceform, and explored. We conducted two user studies to assess our approach, demonstrating that it is an initial positive step towards the successful creation of interactive and engaging anatomical physicalizations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 195, "name": "raidou_slicedice-image.png", "type": "image/png", "size": 51885, "path": "Publication:raidou_slicedice", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 166, 1464 ], "cfp": { "name": "For Authors - PG2020.pdf", "type": "application/pdf", "error": "0", "size": "248544", "orig_name": "For Authors - PG2020.pdf", "ext": "pdf" }, "date_from": "2020", "date_to": "2020", "event": "PG2020", "journal": "Computer Graphics Forum (CGF)", "lecturer": [ 1410 ], "pages_from": "1", "pages_to": "12", "volume": "x", "research_areas": [ "MedVis" ], "keywords": [ "Data Physicalization", "Life and Medical Sciences", "Anatomical Education" ], "weblinks": [], "files": [ { "description": null, "filetitle": "example", "main_file": true, "use_in_gallery": false, "access": "public", "name": "raidou_slicedice-example.pdf", "type": "application/pdf", "size": 1447424, "path": "Publication:raidou_slicedice", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-example.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-example:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 195, "name": "raidou_slicedice-image.png", "type": "image/png", "size": 51885, "path": "Publication:raidou_slicedice", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "preview_image_width": 3045, "preview_image_height": 3045, "name": "raidou_slicedice-paper.pdf", "type": "application/pdf", "size": 20867356, "path": "Publication:raidou_slicedice", "preview_name": "raidou_slicedice-paper:preview.jpg", "preview_type": "image/jpeg", "preview_size": 1021219, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_slicedice-video.mp4", "type": "video/mp4", "size": 166880657, "path": "Publication:raidou_slicedice", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/raidou_slicedice-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_slicedice/", "__class": "Publication" }, { "id": "schindler_2020vis", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58250", "title": "The Anatomical Edutainer", "date": "2020-10", "abstract": "Physical visualizations (i.e., data representations by means of physical objects) have been used for many centuries in medical and anatomical education. Recently, 3D printing techniques started also to emerge. Still, other medical physicalizations that rely on affordable and easy-to-find materials are limited, while smart strategies that take advantage of the optical properties of our physical world have not been thoroughly investigated. We propose the Anatomical Edutainer, a workflow to guide the easy, accessible, and affordable generation of physicalizations for tangible, interactive anatomical edutainment. The Anatomical Edutainer supports 2D printable and 3D foldable physicalizations that change their visual properties (i.e., hues of the visible spectrum) under colored lenses or colored lights, to reveal distinct anatomical structures through user interaction.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "schindler_2020vis-image.png", "type": "image/png", "size": 75476, "path": "Publication:schindler_2020vis", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1760, 1464, 1410 ], "booktitle": "IEEE Vis Short Papers 2020", "cfp": { "name": "Short Paper Call for Participation.pdf", "type": "application/pdf", "error": "0", "size": "132515", "orig_name": "Short Paper Call for Participation.pdf", "ext": "pdf" }, "event": "IEEE Vis 2020", "lecturer": [ 1410 ], "pages_from": "1", "pages_to": "5", "research_areas": [ "Fabrication", "IllVis", "MedVis", "Perception" ], "keywords": [ "Data Physicalization", "Medical Visualization", "Anatomical Education" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "schindler_2020vis-image.png", "type": "image/png", "size": 75476, "path": "Publication:schindler_2020vis", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper preprint", "main_file": true, "use_in_gallery": false, "access": "public", "preview_image_width": 416, "preview_image_height": 421, "name": "schindler_2020vis-paper preprint.pdf", "type": "application/pdf", "size": 26317989, "path": "Publication:schindler_2020vis", "preview_name": "schindler_2020vis-paper preprint:preview.JPG", "preview_type": "image/jpeg", "preview_size": 43449, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-paper preprint.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/schindler_2020vis-paper preprint:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler_2020vis/", "__class": "Publication" }, { "id": "cmolik-2020-tvcg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/58318", "title": "Mixed Labeling: Integrating Internal and External Labels", "date": "2020-09-28", "abstract": "In this paper, we present an algorithm capable of mixed labeling of 2D and 3D objects. In mixed labeling, the given objects are labeled with both internal labels placed (at least partially) over the objects and external labels placed in the space around the objects and connected with the labeled objects with straight-line leaders. The proposed algorithm determines the position and type of each label based on the user-specified ambiguity threshold and eliminates overlaps between the labels, as well as between the internal labels and the straight-line leaders of external labels. The algorithm is a screen-space technique; it operates in an image where the 2D objects or projected 3D objects are encoded. In other words, we can use the algorithm whenever we can render the objects to an image, which makes the algorithm fit for use in many domains. The algorithm operates in real-time, giving the results immediately. Finally, we present results from an expert evaluation, in which a professional illustrator has evaluated the label layouts produced with the proposed algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1246, 1782, 1464, 1579 ], "doi": "10.1109/TVCG.2020.3027368", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "pages_from": "1", "pages_to": "14", "volume": "x", "research_areas": [ "BioVis", "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "cmolik-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 12960199, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/", "__class": "Publication" }, { "id": "Groeller_V3_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87183", "title": " Interactive Visual Data Analysis", "date": "2020-09-19", "abstract": "Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analyses, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. Several examples of interactively and visually analyzing data will be discussed in detail. These include: geospatial decision support, radiation therapy planning, and integrative cell biology. Given the amplified data variability, interactive visual data analyses are likely to gain in importance in the future. Research challenges and directions are sketched at the end of the talk.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "Conference on Image and Graphics Technology and Application (IGTA) 2021", "location": "Bejing ", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "http://www.bsig.org.cn/detail/2420", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V3_2020/", "__class": "Publication" }, { "id": "Iijima-2020-iV", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58172", "title": "Visualization of Semantic Differential Studies with a Large Number of Images, Participants and Attributes", "date": "2020-09-07", "abstract": "The Semantic Differential (SD) Method is a rating scale to measure the semantics. Attributes of SD are constructed by collecting the responses of participant’s impres- sions of the objects expressed through Likert scales representing multiple contrasting with some adjective pairs, for example, dark and bright, formal and casual, etc. Impression evaluation can be used as an index that reflects a human subjective feelings to some extent. Impression evaluations using the SD method consist of the responses of many participants, and therefore, the individual differences in the impressions of the participants greatly affect the content of the data. In this study, we propose a visualization system to analyze three aspects of SD, objects (images), participants, and attributes defined by adjective pairs. We visualize the impression evaluation data by applying dimension reduction so that, users can discover the trends and outliers of the data, such as images that are hard to judge or participants that act unpredictably. The system firstly visualizes the attributes or color distribution of the images by applying a dimensional reduction method to the impression or RGB values of each image. Then, our approach displays the average and median of each attribute near the images. This way, we can visualize the three aspects of objects, participants and attributes on a single screen and observe the relationships between image features and user impressions / attribute space. We introduce visualization examples of our system with the dataset inviting 21 participants who performed impression evaluations with 300 clothing images.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 479, "image_height": 339, "name": "Iijima-2020-iV-image.png", "type": "image/png", "size": 104231, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1787, 1754, 1464, 1366 ], "booktitle": "Proceedings of the 24th International Conference on Information Visualisation (iV2020)", "cfp": { "name": "CFP-iV2020.pdf", "type": "application/pdf", "error": "0", "size": "59112", "orig_name": "CFP-iV2020.pdf", "ext": "pdf" }, "event": "The 24th International Conference on Information Visualisation (iV2020)", "lecturer": [ 1787 ], "pages_from": "1", "pages_to": "6", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 479, "image_height": 339, "name": "Iijima-2020-iV-image.png", "type": "image/png", "size": 104231, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Iijima-2020-iV-paper.pdf", "type": "application/pdf", "size": 4114864, "path": "Publication:Iijima-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/Iijima-2020-iV-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Iijima-2020-iV/", "__class": "Publication" }, { "id": "Kuroko-2020-iV", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58251", "title": "Visualization of Correlations between Places of Music Listening and Acoustic Features ", "date": "2020-09-07", "abstract": "Users often choose songs with respect to special situations and environments. We designed and developed a music recommendation method inspired by this fact. This method selects songs based on the distribution of acoustic features of the songs listened by a user at particular places that have higher ordinariness for the user. It is important to verify the relationship between the places where the songs are listened to and the acoustic features in this. Hence, we conducted the visualization to explore potential correlations between geographic locations and the music features of single users. In this paper, we designed an interactive visualization tool methods and results for the analysis of the relationship between the places and the acoustic features while listening to the songs.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 491, "image_height": 364, "name": "Kuroko-2020-iV-image.png", "type": "image/png", "size": 94249, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1785, 1786, 1754, 1366, 1464 ], "booktitle": "Proceedings of the 24th International Conference on Information Visualisation (iV2020)", "cfp": { "name": "CFP-iV2020.pdf", "type": "application/pdf", "error": "0", "size": "59112", "orig_name": "CFP-iV2020.pdf", "ext": "pdf" }, "event": "The 24th International Conference on Information Visualisation (iV2020)", "lecturer": [ 1785 ], "pages_from": "1", "pages_to": "6", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 491, "image_height": 364, "name": "Kuroko-2020-iV-image.png", "type": "image/png", "size": 94249, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Kuroko-2020-iV-paper.pdf", "type": "application/pdf", "size": 1282476, "path": "Publication:Kuroko-2020-iV", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/Kuroko-2020-iV-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kuroko-2020-iV/", "__class": "Publication" }, { "id": "Purchase-2020-gd", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58252", "title": "The Turing Test for Graph Drawing Algorithms", "date": "2020-09", "abstract": "DoalgorithmsfordrawinggraphspasstheTuringTest?That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on ‘small’ graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing al- gorithms, although this is not always the case for graphs drawn by force- directed or multi-dimensional scaling algorithms, making these good can- didates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Purchase-2020-gd-image.png", "type": "image/png", "size": 29720, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1623, 1619, 1783, 1579, 1784, 1464 ], "booktitle": "Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD2020)", "cfp": { "name": "gd20-cfp.pdf", "type": "application/pdf", "error": "0", "size": "182950", "orig_name": "gd20-cfp.pdf", "ext": "pdf" }, "event": "28th International Symposium on Graph Drawing and Network Visualization ", "lecturer": [ 1623 ], "pages_from": "1", "pages_to": "16", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Purchase-2020-gd-image.png", "type": "image/png", "size": 29720, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Purchase-2020-gd-paper.pdf", "type": "application/pdf", "size": 3933269, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/", "__class": "Publication" }, { "id": "Presch_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15583", "title": "Semi-Automatic Creation of Concept Maps", "date": "2020-08-20", "abstract": "Concept maps are a method for the visualization of knowledge and an established tool in education, knowledge organization and a variety of other fields. They are composed of concepts and interlinked relations between them and are displayed as a node-link diagram. Concept map mining is the process of extracting concept maps from unstructured text. The three approaches to mine concept maps are: manual, semi-automatic or fully automatic. A fully automatic approach cannot mirror the mental knowledge model, which a user would transfer to a manually created concept map. The manual process is often perceived as tedious and ineÿcient, limiting a wide-range application of concept maps.\nThis thesis presents a semi-automatic concept map mining approach that tries to bridge the gap between all manual construction and fully automatic approaches. The advantage of this approach is that the users still have control over how their concept map is constructed, but are not impeded by manual tasks that are often repetitive and ineÿcient. The presented approach is composed of an automatic text processing part, which extracts concepts and relations out of an unstructured text document and is powered by state-of-the-art natural language processing and neural coreference resolution. The second manual concept map creation part allows the creation of concept maps in a user interface and presents the extracted concepts and relations as suggestions to the user.\nIn a user study, an implemented prototype of the proposed semi-automatic concept map mining approach was evaluated. Manual gold standard concept maps that were created by the users and concept maps created by a fully automatic tool were compared to concept maps that were created with the prototype, proving the usefulness of the process. Results show that concept maps created with the semi-automatic prototype are significantly more similar to the gold standard than the ones created by the fully automatic tool. Additionally, considerably improved eÿciency in creation duration and user satisfaction could be observed in comparison to the manual creation of the gold standard maps.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 654, "name": "Presch_2020-teaser.png", "type": "image/png", "size": 262144, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1687 ], "co_supervisor": [ 1110 ], "date_end": "2020-08-20", "date_start": "2020-01-23", "diploma_examina": "2020-08-20", "doi": "10.34726/hss.2020.70123", "matrikelnr": "0602554", "open_access": "yes", "pages": "122", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "Concept Map", "Natural language processing", "NLP" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Presch_2020-Master Thesis.pdf", "type": "application/pdf", "size": 5681227, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Presch_2020-Poster.pdf", "type": "application/pdf", "size": 743440, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1423, "image_height": 654, "name": "Presch_2020-teaser.png", "type": "image/png", "size": 262144, "path": "Publication:Presch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/Presch_2020-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Presch_2020/", "__class": "Publication" }, { "id": "Bechtold2020", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Getting Insight on Animal Behaviour through Interactive Visualization of Multiple T-Maze Ensembles", "date": "2020-08-20", "abstract": "behaviourists and ethologists study cognitive abilities such as learning and memory in rodents to get a better understanding of how similar processes in humans proceed. Often such studies are based on experiments of rodents placed and observed in a Multiple T-Maze. There, the path of the animals are recorded as they move inside the maze, and the resulting trajectories are then analysed. State-of-the-art analysis is based on descriptive parameters and standard statistics where one trajectory at a time is analysed. Usually it is not possible to examine multiple animal paths simultaneously. Together with experts on the field we abstracted the typical work-flow of such analyses and developed an interactive visual analytics tool, with the goal to facilitate the experts’ work and enable a deeper and novel understanding of the learning ability and decision making in rodents. After giving an overview of related works and computer-aided analysis tools in the beginning, the analysis demands and task-breakdown is presented, followed by an Explanation of the data acquisition process, data preprocessing and aggregation. The underlying data structure will be explained as well. The developed analysis tool — the T-Maze Explorer — supports multiple, linked views, which support several traditional methods of visualizations, as well as two newly proposed visualizations fitted to meet the experts’ analysis demands. The first view — the T-Maze View — displays all trajectories of an ensemble with additional options such as highlighting the return path. The purpose of the second view — the Gate-O-Gon view — is to extract information from the trajectories on how often returns in the path occurred and between which parts of the maze these occurred. This information is depicted in a compact and informative novel visualization. The purpose of the T-Maze Explorer is to enable its user to easily find patterns in the data and identify irregular behaviour while inspecting a single path, multiple or the whole trajectory ensemble simultaneously. This thesis provides an insight on how the proposed visualizations were developed, the T-Maze Explorer’s characteristics and benefits as well as it’s limitations. Lastly, a brief excerpt is given on how the T-Maze Explorer could be extended in the future.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 341, "image_height": 306, "name": "Bechtold2020-image.JPG", "type": "image/jpeg", "size": 23611, "path": "Publication:Bechtold2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1778 ], "date_end": "2020-08-20", "date_start": "2020-03-02", "matrikelnr": "00827420", "supervisor": [ 235 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Bechtold2020-Bachelor thesis.pdf", "type": "application/pdf", "size": 1852939, "path": "Publication:Bechtold2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-Bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-Bachelor thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 341, "image_height": 306, "name": "Bechtold2020-image.JPG", "type": "image/jpeg", "size": 23611, "path": "Publication:Bechtold2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/Bechtold2020-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Bechtold2020/", "__class": "Publication" }, { "id": "Stoll2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15401", "title": " Tactile Multi-Media Guide - Interaction design on tactile reliefs", "date": "2020-08-18", "abstract": "This thesis was part of the three year ARCHES project. We have set ourselves the goal to create an inclusive cultural environment. The main contribution of this thesis is the development of a new Tactile Multi-Media Guide (TMG). The TMG is an interaction design on tactile reliefs, which makes art accessible for visitors with various visual, hearing and cognitive access preferences. Over 200 people with diverse disabilities from participatory research groups in London, Madrid, Oviedo and Vienna met in the museums, developed ideas, tested and helped shape the prototypes. This thesis establishes a Design for all mixed reality prototype, where users can explore six artworks with their hands and trigger information with specific gestures. The TMG provides information in form of audio files, subtitles, sign language videos, as well as texts. It also supports visitors with learning difficulties with an easy read version. This thesis shows that experiencing art can be interesting and accessible for everyone. ", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 500, "image_height": 667, "name": "Stoll2020-Image.jpg", "type": "image/jpeg", "size": 80416, "path": "Publication:Stoll2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1810 ], "date_end": "2020-08-18", "date_start": "2019-09-20", "diploma_examina": "2020-08-18", "doi": "10.34726/hss.2020.58901", "matrikelnr": "00804929", "open_access": "yes", "pages": "87", "supervisor": [ 190 ], "research_areas": [ "IllVis" ], "keywords": [ "Interaction", "human-centered design", "multimedia", "tactile" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 500, "image_height": 667, "name": "Stoll2020-Image.jpg", "type": "image/jpeg", "size": 80416, "path": "Publication:Stoll2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Stoll2020-Master Thesis.pdf", "type": "application/pdf", "size": 3591058, "path": "Publication:Stoll2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Stoll2020-Poster.pdf", "type": "application/pdf", "size": 4009292, "path": "Publication:Stoll2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/Stoll2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Stoll2020/", "__class": "Publication" }, { "id": "riegler_2020_framework", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "High-Performance Framework for Dataset Generation", "date": "2020-08-05", "abstract": "The aim of this bachelor thesis is the development of a Python framework. The main task for this framework is the generation of datasets, which can be further used for surface reconstruction. They are needed for training a neural network, which is then able to reconstruct meshes on its own given a point cloud of a mesh. In order to optimize the training of the neural network, a lot of training data is needed. This framework utilizes multi-processing to achieve a faster generation process in comparison to sequentially generating one mesh after another.\n\nIn addition, the framework is also able to handle any kind of similar pipeline. The user is able to define the steps of such pipeline in an XML document, which then can make calls to arbitrary programs. This fact makes the framework an all-purpose tool for any kind of task that needs to process a lot of data independent from each other.\n\nThe results show a great performance increase when generating datasets. This can be seen in the benchmarks that have been done. The time of execution for a fixed amount of files has been measured with different modes of execution. The custom process pool we developed shows a faster time overall compared to using Python's process pool for each step of the pipeline independently. It is also way faster in comparison to running every step for each file sequentially.", "authors_et_al": false, "substitute": null, "main_image": { "description": "The processing steps of the dataset generation shown as a graph.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1229, "image_height": 755, "name": "riegler_2020_framework-teaser.png", "type": "image/png", "size": 87801, "path": "Publication:riegler_2020_framework", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1758 ], "date_end": "2020-08-05", "date_start": "2020-04-02", "matrikelnr": "1634877", "supervisor": [ 1395 ], "research_areas": [ "Geometry" ], "keywords": [ "dataset generation", "framework", "surface reconstruction" ], "weblinks": [], "files": [ { "description": "The processing steps of the dataset generation shown as a graph.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1229, "image_height": 755, "name": "riegler_2020_framework-teaser.png", "type": "image/png", "size": 87801, "path": "Publication:riegler_2020_framework", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": true, "access": "public", "name": "riegler_2020_framework-thesis.pdf", "type": "application/pdf", "size": 708911, "path": "Publication:riegler_2020_framework", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/riegler_2020_framework-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/riegler_2020_framework/", "__class": "Publication" }, { "id": "honic-2020-w78", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/62920", "title": "Scan to BIM for the Semi-Automated Generation of a Material Passport for an Existing Building", "date": "2020-08", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1798, 1799, 1800, 193 ], "booktitle": " Proceedings of the 37th International Conference of CIB W78", "cfp": { "name": "ICCCBE-CIBW78 2020 in São Paulo - Brazil.pdf", "type": "application/pdf", "error": "0", "size": "733465", "orig_name": "ICCCBE-CIBW78 2020 in São Paulo - Brazil.pdf", "ext": "pdf" }, "event": "Proceedings of the 37th International Conference of CIB W78, Sao Paulo - online", "pages_from": "338", "pages_to": "346", "research_areas": [ "Modeling" ], "keywords": [], "weblinks": [ { "href": "https://itc.scix.net/paper/w78-2020-paper-024", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/honic-2020-w78/", "__class": "Publication" }, { "id": "OTEPKA-2020-PPC", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Efficient Loading and Visualization of Massive Feature-Richt Point Clouds Without Hierarchical Acceleration Structures", "date": "2020-08", "abstract": "Nowadays, point clouds are the standard product when capturing reality independent of scale and measurement technique. Especially, Dense Image Matching (DIM) and Laser Scanning (LS) are state of the art capturing methods for a great variety of applications producing detailed point clouds up to billions of points. In-depth analysis of such huge point clouds typically requires sophisticated spatial indexing structures to support potentially long-lasting automated non-interactive processing tasks like feature extraction, semantic labelling, surface generation, and the like. Nevertheless, a visual inspection of the point data is often necessary to obtain an impression of the scene, roughly check for completeness, quality, and outlier rates of the captured data in advance. Also intermediate processing results, containing additional per-point computed attributes, may require visual analyses to draw conclusions or to parameterize further processing. Over the last decades a variety of commercial, free, and open source viewers have been developed that can visualise huge point clouds and colorize them based on available attributes. However, they have either a poor loading and navigation performance, visualize only a subset of the points, or require the creation of spatial indexing structures in advance. In this paper, we evaluate a progressive method that is capable of rendering any point cloud that fits in GPU memory in real time without the need of time consuming hierarchical acceleration structure generation. In combination with our multi-threaded LAS and LAZ loaders, we achieve load performance of up to 20 million points per second, display points already while loading, support flexible switching between different attributes, and rendering up to one billion points with visually appealing navigation behaviour. Furthermore, loading times of different data sets for different open source and commercial software packages are analysed.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 521, "image_height": 591, "name": "OTEPKA-2020-PPC-image.jpg", "type": "image/jpeg", "size": 59602, "path": "Publication:OTEPKA-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1701, 1700, 1116, 1797, 193 ], "cfp": { "name": "isprs-archives-XLIII-B2-2020-1-2020.pdf", "type": "application/pdf", "error": "0", "size": "1916748", "orig_name": "isprs-archives-XLIII-B2-2020-1-2020.pdf", "ext": "pdf" }, "date_from": "2020-08-31", "date_to": "2020-09-02", "doi": "10.5194/isprs-archives-XLIII-B2-2020-293-2020", "event": "XXIV ISPRS Congress (2020 edition)", "issn": "1682-1750", "journal": "ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences", "lecturer": [ 1701 ], "location": "online", "open_access": "yes", "pages_from": "293", "pages_to": "300", "volume": "XLIII-B2-2020", "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 521, "image_height": 591, "name": "OTEPKA-2020-PPC-image.jpg", "type": "image/jpeg", "size": 59602, "path": "Publication:OTEPKA-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "OTEPKA-2020-PPC-paper.pdf", "type": "application/pdf", "size": 17113367, "path": "Publication:OTEPKA-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/OTEPKA-2020-PPC-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "External", "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/OTEPKA-2020-PPC/", "__class": "Publication" }, { "id": "Sebernegg2020", "type_id": "techreport", "tu_id": null, "repositum_id": "20.500.12708/40238", "title": "Motion Similarity Modeling - A State of the Art Report", "date": "2020-08", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "MoSiMo", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1278, "image_height": 887, "name": "Sebernegg2020-MoSiMo.jpg", "type": "image/jpeg", "size": 148448, "path": "Publication:Sebernegg2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Sebernegg2020/Sebernegg2020-MoSiMo.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Sebernegg2020/Sebernegg2020-MoSiMo:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1804, 1720, 378 ], "number": "TR-193-02-2020-5", "open_access": "yes", "research_areas": [ "VR" ], "keywords": [], "weblinks": [ { "href": "https://arxiv.org/abs/2008.05872", "caption": "arXiv", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "MoSiMo", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1278, "image_height": 887, "name": "Sebernegg2020-MoSiMo.jpg", "type": "image/jpeg", "size": 148448, "path": "Publication:Sebernegg2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Sebernegg2020/Sebernegg2020-MoSiMo.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Sebernegg2020/Sebernegg2020-MoSiMo:thumb{{size}}.png" } ], "projects_workgroups": [ "vr" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Sebernegg2020/", "__class": "Publication" }, { "id": "freude_2020_rs", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "R-Score: A Novel Approach to Compare Monte Carlo Renderings", "date": "2020-08", "abstract": "In this paper, we propose a new approach for the comparison and analysis of Monte Carlo (MC) rendering algorithms. It is based on a novel similarity measure called render score (RS) that is specically designed for MC rendering, statistically motivated, and incorporates bias and variance. Additionally, we propose a comparison scheme that alleviates the need for practically converged reference images (RIs). Our approach can be used to compare and analyze dierent rendering methods by revealing detailed (per-pixel) dierences and subsequently potential conceptual or implementation-related issues, thereby offering a more informative and meaningful alternative to commonly used metrics.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser-image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 630, "image_height": 533, "name": "freude_2020_rs-teaser-image.png", "type": "image/png", "size": 89069, "path": "Publication:freude_2020_rs", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-teaser-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-teaser-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1128, 1129, 1073, 193 ], "number": "TR-193-02-2020-4", "open_access": "no", "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser-image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 630, "image_height": 533, "name": "freude_2020_rs-teaser-image.png", "type": "image/png", "size": 89069, "path": "Publication:freude_2020_rs", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-teaser-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-teaser-image:thumb{{size}}.png" }, { "description": null, "filetitle": "technical-report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "freude_2020_rs-technical-report.pdf", "type": "application/pdf", "size": 1215341, "path": "Publication:freude_2020_rs", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-technical-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/freude_2020_rs-technical-report:thumb{{size}}.png" } ], "projects_workgroups": [ "OpenData" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/freude_2020_rs/", "__class": "Publication" }, { "id": "brugger-2020-tdp", "type_id": "misc", "tu_id": null, "repositum_id": null, "title": "Test Scene Design for Physically Based Rendering", "date": "2020-08", "abstract": "Physically based rendering is a discipline in computer graphics which aims at reproducing certain light and material appearances that occur in the real world. Complex scenes can be difficult to compute for rendering algorithms. This paper introduces a new comprehensive test database of scenes that treat different light setups in conjunction with diverse materials and discusses its design principles. A lot of research is focused on the development of new algorithms that can deal with difficult light conditions and materials efficiently. This database delivers a comprehensive foundation for evaluating existing and newly developed rendering techniques. A final evaluation compares different results of different rendering algorithms for all scenes.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser-image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1600, "image_height": 900, "name": "brugger-2020-tdp-teaser-image.png", "type": "image/png", "size": 1883053, "path": "Publication:brugger-2020-tdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-teaser-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-teaser-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1780, 1128, 193 ], "open_access": "no", "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [ { "href": "https://arxiv.org/abs/2008.11657", "caption": "arXiv", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "brugger-2020-tdp-paper.pdf", "type": "application/pdf", "size": 45483139, "path": "Publication:brugger-2020-tdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser-image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1600, "image_height": 900, "name": "brugger-2020-tdp-teaser-image.png", "type": "image/png", "size": 1883053, "path": "Publication:brugger-2020-tdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-teaser-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/brugger-2020-tdp-teaser-image:thumb{{size}}.png" } ], "projects_workgroups": [ "OpenData" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tdp/", "__class": "Publication" }, { "id": "Nowak_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/16969", "title": "Hierarchical Multi-resolution Data Structure for Molecular Visualization", "date": "2020-07-27", "abstract": "The complexity of biomolecular data sets is both high, and still rising. Three-dimensional models of molecules are used in research to test and investigate their properties. Such models can consist of several millions of atoms. Additionally, visual enhancement methods\nand molecular surface models are helpful when visualizing molecules. There is therefore a demand for efficient and flexible data structures to accommodate such large point-based data sets.\nExisting solutions in the field of molecular visualization for large data sets include the use of, in most cases, regular grid-based data structures, as well as levels of detail. Other papers focus on repeating structures or improving the efficiency of surface models.\nWe propose an octree-based data structure that divides space into areas of similar density, and provides several levels of detail. Our approach is optimized for a single time-step, moving much of the computational overhead into a pre-processing step. This allows us to speed up frame rates for interactive visualizations using visibility culling, least recently used caching based on the pre-built octree data structure, and level of detail solutions such as depth-based level of detail rendering.\nIn our evaluation, we show that level of detail rendering significantly improves frame rates, especially in the case of distance-based level of detail selection while keeping the amount of details in the foreground high. Both the possibility to reduce the resolution and the\ncaching strategy that allows us to only upload visible parts of the data set make it possible to render data sets that previously exhausted the capacities of our test set-up. We found the main advantage of a density based octree, instead of a regular division of space, to be\nin neighbourhood-based calculations, such as the clustering algorithm required to build levels of detail. This could prove particularly useful for the implementation of a Solvent Excluded Surface (SES) representation model, which would be an important feature to include when developing the framework further.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1068, "image_height": 324, "name": "Nowak_2020-Image.JPG", "type": "image/jpeg", "size": 105988, "path": "Publication:Nowak_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1923 ], "date_end": "2020-07-27", "date_start": "2010-02-21", "diploma_examina": "2020-07-27", "doi": "10.34726/hss.2021.53962", "matrikelnr": "0927584", "open_access": "yes", "pages": "110", "supervisor": [ 161 ], "research_areas": [ "BioVis" ], "keywords": [ "Molecular Visualization", "Real-Time Rendering", "Computer Graphics" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1068, "image_height": 324, "name": "Nowak_2020-Image.JPG", "type": "image/jpeg", "size": 105988, "path": "Publication:Nowak_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Nowak_2020-Master Thesis.pdf", "type": "application/pdf", "size": 4783960, "path": "Publication:Nowak_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/Nowak_2020-Master Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Nowak_2020/", "__class": "Publication" }, { "id": "Neubauer2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15249", "title": "Volumetric Image Segmentation on Multimodal Medical Images using Deep Learning", "date": "2020-07-25", "abstract": "The automatic segmentation of tumors on different imaging modalities supports medical experts in patient diagnosis and treatment. Magnetic resonance imaging (MRl), Computed Tomography (CT), or Positron Emission Tomography (PET) show the tumor in a different anatomical. functional, or molecular context. The fusion of this multimodal information leads to more profound knowledge and enabler more precise diagnoses. So far, the potential of multimodal data is only used by a few established segmentation methods. Moreover, much less is known about multimodal methods that provide several multimodal-specific tumor segmentations instead of single segmentations for a specific modality. \nThis thesis aims to develop a segmentation method that uses multimodal context to improve t the modality-specific segmentation results. For the implementation, an artificial neural network is used, which is based on a fully convolution neural network. The network architecture has been designed to learn complex multimodal features to predict multiple tumor segmentations on different modalities efficiently. \nThe evaluation is based on a dataset consisting of MRl aid PET /CT scans of soft soft tissue tumors. The experiment investigated how different network architectures, multimodal fusion strategies, and input modalities affect the segmentation results. Tbc investigation showed that multimodal rondels lead to significantly better results than models for single modalities. Promising results have been achieved with multimodal models that segment several modality-specific tumor contours simultaneously.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 236, "image_height": 286, "name": "Neubauer2020-image.JPG", "type": "image/jpeg", "size": 23529, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1777 ], "co_supervisor": [ 231 ], "date_end": "2020-07-25", "date_start": "2019-12-10", "diploma_examina": "2020-08-05", "doi": "10.34726/hss.2020.73220", "matrikelnr": "01609920", "open_access": "yes", "pages": "118", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "tumor segmentation", "deep learning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 236, "image_height": 286, "name": "Neubauer2020-image.JPG", "type": "image/jpeg", "size": 23529, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Neubauer2020-Master Thesis.pdf", "type": "application/pdf", "size": 9032923, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Neubauer2020-Poster.pdf", "type": "application/pdf", "size": 9820244, "path": "Publication:Neubauer2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/Neubauer2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Neubauer2020/", "__class": "Publication" }, { "id": "kerbl-2020-improvencoding", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "Improved Triangle Encoding for Cached Adaptive Tessellation", "date": "2020-07", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Lod", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1680, "image_height": 850, "name": "kerbl-2020-improvencoding-Lod.png", "type": "image/png", "size": 19386, "path": "Publication:kerbl-2020-improvencoding", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-Lod.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-Lod:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1772, 1650, 193 ], "cfp": { "name": "cfp.pdf", "type": "application/pdf", "error": "0", "size": "1255664", "orig_name": "cfp.pdf", "ext": "pdf" }, "date_from": "2020-05-01", "date_to": "2020-06-22", "event": "HPG 2020", "location": "online", "open_access": "yes", "research_areas": [ "Rendering" ], "keywords": [ "GPU", "tessellation", "real-time" ], "weblinks": [ { "href": "https://www.highperformancegraphics.org/2020/program/", "caption": "HPG 2020 page with download link", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "Lod", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1680, "image_height": 850, "name": "kerbl-2020-improvencoding-Lod.png", "type": "image/png", "size": 19386, "path": "Publication:kerbl-2020-improvencoding", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-Lod.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-Lod:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kerbl-2020-improvencoding-paper.pdf", "type": "application/pdf", "size": 2356615, "path": "Publication:kerbl-2020-improvencoding", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kerbl-2020-improvencoding-poster.pdf", "type": "application/pdf", "size": 1126638, "path": "Publication:kerbl-2020-improvencoding", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "terrain", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1680, "image_height": 850, "name": "kerbl-2020-improvencoding-terrain.png", "type": "image/png", "size": 1397504, "path": "Publication:kerbl-2020-improvencoding", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-terrain.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/kerbl-2020-improvencoding-terrain:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kerbl-2020-improvencoding/", "__class": "Publication" }, { "id": "miao_nar_2020", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141025", "title": "Adenita: interactive 3D modelling and visualization of DNA nanostructures", "date": "2020-07", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1229, "preview_image_height": 579, "name": "miao_nar_2020-.pdf", "type": "application/pdf", "size": 1444761, "path": "Publication:miao_nar_2020", "preview_name": "miao_nar_2020-:preview.png", "preview_type": "image/png", "preview_size": 391675, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/miao_nar_2020/miao_nar_2020-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/miao_nar_2020/miao_nar_2020-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1474, 1263, 1471, 1774, 1775, 171, 1473 ], "doi": "10.1093/nar/gkaa593", "journal": "Nucleic Acids Research", "research_areas": [ "BioVis", "IllVis", "Modeling" ], "keywords": [], "weblinks": [ { "href": "https://academic.oup.com/nar/article-pdf/doi/10.1093/nar/gkaa593/33517747/gkaa593.pdf", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1229, "preview_image_height": 579, "name": "miao_nar_2020-.pdf", "type": "application/pdf", "size": 1444761, "path": "Publication:miao_nar_2020", "preview_name": "miao_nar_2020-:preview.png", "preview_type": "image/png", "preview_size": 391675, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/miao_nar_2020/miao_nar_2020-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/miao_nar_2020/miao_nar_2020-:thumb{{size}}.png" } ], "projects_workgroups": [ "Illustrare" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/miao_nar_2020/", "__class": "Publication" }, { "id": "reznicek-2020-fpgaray", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15010", "title": "FPGARay: Accelerating Physically Based Rendering Using FPGAs", "date": "2020-06-30", "abstract": "The synthesis of an image from a scene stored on a computer is called rendering, which is able to deliver photo-realistic results, e.g., by using specific variants of the class of ray tracing\nalgorithms. However, these variants (e.g., path tracing) possess a stochastic characteristic which results in a high computational expense. This is explained by the nature of stochastic algorithms, which use a high number of samples to compute a result—in case of ray tracing, these samples manifest in a high number of rays needed for a complete rendering.\n\nOne possibility to accelerate ray tracing—no matter if using a stochastic or simpler variants—is the use of customized hardware. FPGRay is such an approach, which combines the use of customized hardware with the software of an off-the-shelf PC to a hybrid solution. This allows increasing the efficiency by specialized hardware and delivers a sustainability in case of changing algorithms at the same time.\n\nThe results point towards a possible efficiency gain. Unfortunately, in the scope of this thesis this was not realizable and the specific implementation showed a lower efficiency compared to the software implementation. Nevertheless, the possibility to achieve a higher efficiency with this approach by indicating FPGRay’s potential could be shown.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2473, "image_height": 1643, "name": "reznicek-2020-fpgaray-image.jpg", "type": "image/jpeg", "size": 222318, "path": "Publication:reznicek-2020-fpgaray", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1541 ], "date_end": "2020-06-30", "date_start": "2017-03-16", "diploma_examina": "2020-06-30", "doi": "10.34726/hss.2020.45543", "matrikelnr": "01125076", "open_access": "yes", "pages": "121", "supervisor": [ 1129, 193 ], "research_areas": [ "Rendering" ], "keywords": [ "Rendering", "FPGA", "hardware acceleration", "ray tracing", "path tracing" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2473, "image_height": 1643, "name": "reznicek-2020-fpgaray-image.jpg", "type": "image/jpeg", "size": 222318, "path": "Publication:reznicek-2020-fpgaray", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "reznicek-2020-fpgaray-poster.pdf", "type": "application/pdf", "size": 758792, "path": "Publication:reznicek-2020-fpgaray", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "reznicek-2020-fpgaray-thesis.pdf", "type": "application/pdf", "size": 19196600, "path": "Publication:reznicek-2020-fpgaray", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/reznicek-2020-fpgaray-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reznicek-2020-fpgaray/", "__class": "Publication" }, { "id": "zsolnaifeher-2020-pme", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/141026", "title": "Photorealistic Material Editing Through Direct Image Manipulation", "date": "2020-06-29", "abstract": "Creating photorealistic materials for light transport algorithms requires carefully fine-tuning a set of material properties to achieve a desired artistic effect. This is typically a lengthy process that involves a trained artist with specialized knowledge. In this work, we present a technique that aims to empower novice and intermediate-level users to synthesize high-quality photorealistic materials by only requiring basic image processing knowledge. In the proposed workflow, the user starts with an input image and applies a few intuitive transforms (e.g., colorization, image inpainting) within a 2D image editor of their choice, and in the next step, our technique produces a photorealistic result that approximates this target image. Our method combines the advantages of a neural network-augmented optimizer and an encoder neural network to produce high-quality output results within 30 seconds. We also demonstrate that it is resilient against poorly-edited target images and propose a simple extension to predict image sequences with a strict time budget of 1-2 seconds per image.\n\nVideo: https://www.youtube.com/watch?v=8eNHEaxsj18", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 883, "image_height": 934, "name": "zsolnaifeher-2020-pme-image.jpg", "type": "image/jpeg", "size": 239774, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1073, 194, 193 ], "cfp": { "name": "[Members] Updated EGSR CFP.eml", "type": "message/rfc822", "error": "0", "size": "23492", "orig_name": "[Members] Updated EGSR CFP.eml", "ext": "eml" }, "date_from": "2020-06-29", "date_to": "2020-07-03", "doi": "10.1111/cgf.14057", "event": "Eurographics Symposium on Rendering 2020", "first_published": "2020-07-20", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1073 ], "location": "London, UK", "number": "4", "open_access": "yes", "pages": "14", "pages_from": "107", "pages_to": "120", "volume": "39", "research_areas": [ "Rendering" ], "keywords": [ "neural rendering", "neural networks", "photorealistic rendering", "photorealistic material editing" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/zsolnai/gfx/photorealistic-material-editing/", "caption": "Source code", "description": null, "main_file": 0 }, { "href": "https://www.youtube.com/watch?v=8eNHEaxsj18", "caption": "Supplementary video", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 883, "image_height": 934, "name": "zsolnaifeher-2020-pme-image.jpg", "type": "image/jpeg", "size": 239774, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image:thumb{{size}}.png" }, { "description": null, "filetitle": "image2", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2768, "image_height": 2959, "name": "zsolnaifeher-2020-pme-image2.jpg", "type": "image/jpeg", "size": 976205, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image2.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image2:thumb{{size}}.png" }, { "description": null, "filetitle": "image3", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2560, "image_height": 1440, "name": "zsolnaifeher-2020-pme-image3.jpg", "type": "image/jpeg", "size": 631004, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image3.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image3:thumb{{size}}.png" }, { "description": null, "filetitle": "image4", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2560, "image_height": 1440, "name": "zsolnaifeher-2020-pme-image4.jpg", "type": "image/jpeg", "size": 666732, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image4.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image4:thumb{{size}}.png" }, { "description": null, "filetitle": "image5", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 3840, "image_height": 2160, "name": "zsolnaifeher-2020-pme-image5.jpg", "type": "image/jpeg", "size": 616892, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image5.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-image5:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "zsolnaifeher-2020-pme-paper.pdf", "type": "application/pdf", "size": 11320226, "path": "Publication:zsolnaifeher-2020-pme", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/zsolnaifeher-2020-pme-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "PathSpace" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/zsolnaifeher-2020-pme/", "__class": "Publication" }, { "id": "purgathofer-2020-nan", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "The Role of Visual Computing in the Digitization Process", "date": "2020-06-23", "abstract": "We are living in interesting times, with the fastest technological development that humankind has ever experienced.\nThe last 200 years have brought us the industrial revolution.\nPeople have learned to build machines to release themselves from hard muscle work and from dangerous work.\nPeople have developed new technologies that enabled the realization of dreams from the past like the telephone, the car, the airplane, electrical light, or radio and television.\nAnd industrialization has enabled the production of enough goods for everyone, so that poverty has a much higher threshold today.\nNow we are in the middle of the information revolution, which tries to improve our lives through computers.\nWe are using electronic banking, social media, Computer Aided Design and Manufacturing, tomography diagnosis in medicine, smartphones, GPS, notebooks, computer games, and there are many more appearances of computers in everyday life.\nCurrently we are developing smart cities, digital twins, intelligent factories, autonomous cars and more.\nOur tools include Artificial Intelligence, Deep Learning, fast communication such as 5G, Cloud Computing, Augmented and Virtual Reality, and many others.\nDigital twins, that are digital representations of real world objects, they are the basis for the simulation and augmentation of scenarios, necessary to provide insight for better human decisions.\nIn this context, Visual Computing plays a central role, as it provides the key technologies to include the human into the decision making processes:\n- as the interface between computers and people, - as the most efficient channel to transfer data into users via images.\nVisual computing was also a main driver in developing parallel computing and the GPU. The full potential of visual computing has not yet been exploited in industrial applications, often because real world data are more difficult to handle that clean test data in science labs.\nSix V’s are the six challenges that we have to cope with in visual data processing:\nThe Volume of data is ever increasing. More and more sensors produce more and more data for more and more computers.\nThe Velocity with which such data is produced is steadily increasing.\nThe Variety of data that shall be utilized is becoming more complex. Not only numerical data, but also categorical data, functions, pictures and videos, complex relations shall be processed.\nThe Validity of available data has to be better checked the more data there are. Are some data wrong? Are data missing?\nThe Veracity of data is the next issue. Where do the data come from? Can we trust the data sources? Are some data manipulated or simply made up?\nAnd finally, the Value of our conclusions and results has to be analyzed. Not everything that can be calculated makes the world better.\nThe coping with these 6 V-challenges is essential for the practical utilization of big data.\nBut there is a seventh issue, the Confidentiality of the data. Companies are reluctant to give away their internal data without control who sees or uses them. And people want to maintain some privacy, they want their private data protected, according to data protection laws. Companies like Google or Amazon, but also governments in many countries, store a lot of data about individuals that contradict with such concerns. It must stay one of our most important goals to preserve enough data protection to avoid any misuse of private data. Big data is only a blessing if it is not misused.\nOur research institute VRVis, together with its Chinese partner VR-KB, works in the field of transferring scientific results from visual computing into valuable and innovative products in industry. International cooperation is a success factor in bringing these fields together.\nAnd international conferences such as this one provide the contacts for international cooperation and better understanding between the diverse disciplines profiting from the digitization process.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 190 ], "event": "Nanjing Tech Week", "location": "Nanjing, China", "research_areas": [], "keywords": [ "visual computing", "digitization" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/purgathofer-2020-nan/", "__class": "Publication" }, { "id": "Pilizar_-2020-bachelor", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Artistic Metro Maps", "date": "2020-06-10", "abstract": "The creation of visually pleasing artistic metro maps usually requires a designer and a lot of effort, and while the automatic generation of regular metro maps has been done via several methods, none focus on the artistic aspect. To make the process easier for designers this thesis introduces a method that automatically creates maps that can either be used as they are, or used as baseline for the future design process. The goal of this thesis is to find a method and based on that create a prototype that generates metro maps in arbitrary shapes that simply requires the map and contour as input. Additional parameters are supposed to allow a user to make adjustments if so desired. The general approach is to first prepare the map as well as the contour for the following least squares calculations that reshape the map in a way to fit the contour and then create the look of a typical metro map. To test the algorithm and showcase its results it is applied to two different maps and seven different shapes. These results indicate that the introduced approach is capable of creating metro maps in arbitrary shapes, but need further adjustments by a designer to finalize the map.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1019, "image_height": 870, "name": "Pilizar_-2020-bachelor-image.png", "type": "image/png", "size": 48994, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1764 ], "date_end": "2020-06", "date_start": "2019-06", "matrikelnr": "01525787", "supervisor": [ 1464 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1019, "image_height": 870, "name": "Pilizar_-2020-bachelor-image.png", "type": "image/png", "size": 48994, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Pilizar_-2020-bachelor-thesis.pdf", "type": "application/pdf", "size": 3508257, "path": "Publication:Pilizar_-2020-bachelor", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/Pilizar_-2020-bachelor-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Pilizar_-2020-bachelor/", "__class": "Publication" }, { "id": "raidou_pingu2020", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58256", "title": "PINGU Principles of Interactive Navigation for Geospatial Understanding", "date": "2020-06", "abstract": "Monitoring conditions in the periglacial areas of Antarctica helps geographers and geologists to understand physical processes associated with mesoscale land systems. Analyzing these unique temporal datasets poses a significant challenge for domain experts, due to the complex and often incomplete data, for which corresponding exploratory tools are not available. In this paper, we present a novel visual analysis tool for extraction and interactive exploration of temporal measurements captured at the polar station at the James Ross Island in Antarctica. The tool allows domain experts to quickly extract information about the snow level, originating from a series of photos acquired by trail cameras. Using linked views, the domain experts can interactively explore and combine this information with other spatial and non-spatial measures, such as temperature or wind speed, to reveal the interplay of periglacial and aeolian processes. An abstracted interactive map of the area indicates the position of measurement spots to facilitate navigation. The design of the tool was made in tight collaboration with geographers, which resulted in an early prototype, tested in the pilot study. The following version of the tool and its usability has been evaluated in the user study with five domain experts and their feedback was incorporated into the final version, presented in this paper. This version was again discussed with two experts in an informal interview. Within these evaluations, they confirmed the significant benefit of the tool for their research tasks.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1766, 1767, 1768, 1769, 1254, 1410, 1248 ], "booktitle": "2020 IEEE Pacific Visualization Symposium (PacificVis)", "cfp": { "name": "PacificVis 2020 call.pdf", "type": "application/pdf", "error": "0", "size": "168569", "orig_name": "PacificVis 2020 call.pdf", "ext": "pdf" }, "doi": "10.1109/PacificVis48177.2020.7567", "event": "IEEE Pacific Vis 2020", "lecturer": [ 1410 ], "pages_from": "216", "pages_to": "225", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1899, "image_height": 943, "name": "raidou_pingu2020-image.bmp", "type": "image/bmp", "size": 5375154, "path": "Publication:raidou_pingu2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-image.bmp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_pingu2020-paper.pdf", "type": "application/pdf", "size": 2925903, "path": "Publication:raidou_pingu2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/raidou_pingu2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_pingu2020/", "__class": "Publication" }, { "id": "wu-2020-eurovis-star", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/140650", "title": "A Survey on Transit Map Layout – from Design, Machine, and Human Perspectives", "date": "2020-05-25", "abstract": "Transit maps are designed to present information for using public transportation systems, such as urban railways. Creating a transit map is a time-consuming process, which requires iterative information selection, layout design, and usability validation, and thus maps cannot easily be customised or updated frequently. To improve this, scientists investigate fully- or semi-automatic techniques in order to produce high quality transit maps using computers and further examine their corresponding usability. Nonetheless, the quality gap between manually-drawn maps and machine-generated maps is still large. To elaborate the current research status, this state-of-the-art report provides an overview of the transit map generation process, primarily from Design, Machine, and Human perspectives. A systematic categorisation is introduced to describe the design pipeline, and an extensive analysis of perspectives is conducted to support the proposed taxonomy. We conclude this survey with a discussion on the current research status, open challenges, and future directions.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-eurovis-star-image.png", "type": "image/png", "size": 20954, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1464, 1675, 1580, 1765, 1579 ], "cfp": { "name": "Eurovis – STARS – Eurographics & Eurovis 2020.pdf", "type": "application/pdf", "error": "0", "size": "468579", "orig_name": "Eurovis – STARS – Eurographics & Eurovis 2020.pdf", "ext": "pdf" }, "date_from": "2020-05-25", "date_to": "2020-05-29", "doi": "10.1111/cgf.14030", "event": "EuRoVis 2020", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1464 ], "number": "3", "open_access": "yes", "pages": "28", "pages_from": "619", "pages_to": "646", "volume": "39", "research_areas": [ "InfoVis" ], "keywords": [ "Computer Graphics and Computer-Aided Design" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-eurovis-star-image.png", "type": "image/png", "size": 20954, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-eurovis-star-paper.pdf", "type": "application/pdf", "size": 13228908, "path": "Publication:wu-2020-eurovis-star", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/wu-2020-eurovis-star-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-eurovis-star/", "__class": "Publication" }, { "id": "Korpitsch-2020-wscg", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58257", "title": "Simulated Annealing to Unfold 3D Meshes and Assign Glue Tabs", "date": "2020-05-19", "abstract": "3D mesh unfolding transforms a 3D mesh model into one or multiple 2D planar patches. The technique is widely used to fabricate papercrafts, where 3D objects can be reconstructed from printed paper or paper-like materials. The applicability, visual quality, and stability of such papercraft productions is still challenging since it requires a reasonable formulation of these factors. In this paper, we unfold a 3D mesh into a single connected 2D patch. We also introduce glue tabs as additional indicators in order to provide users with extra space to apply glue for better reconstruction quality. To improve space efficiency, we do not apply glue tabs on every edge, while still guaranteeing the stability of the constructed paper model. A minimum spanning tree (MST) describes possible unfoldings, whereas simulated annealing optimisation is used to find an optimal unfolding. Our approach allows us to unfold 3D triangular meshes into single 2D patches without shape distortions, and employing only a small number of glue tabs. A visual indicator scheme is also incorporated as a post-process to guide users during the model reconstruction process. Finally, we qualitatively evaluate the applicability of the presented approach in comparison to the conventional technique and the achieved results.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Korpitsch-2020-wscg-image.png", "type": "image/png", "size": 49162, "path": "Publication:Korpitsch-2020-wscg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1697, 1580, 166, 1464 ], "booktitle": "Proceedings of the 28th International Conference in Central Europe on Computer Graphics", "cfp": { "name": "wscg-cfp.pdf", "type": "application/pdf", "error": "0", "size": "1699728", "orig_name": "wscg-cfp.pdf", "ext": "pdf" }, "date_from": "2020-05-19", "date_to": "2020-05-21", "event": "WSCG 2020", "lecturer": [ 1464 ], "pages_from": "1", "pages_to": "10", "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Korpitsch-2020-wscg-image.png", "type": "image/png", "size": 49162, "path": "Publication:Korpitsch-2020-wscg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Korpitsch-2020-wscg-paper.pdf", "type": "application/pdf", "size": 19530461, "path": "Publication:Korpitsch-2020-wscg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Korpitsch-2020-wscg-video.mp4", "type": "video/mp4", "size": 10733469, "path": "Publication:Korpitsch-2020-wscg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/Korpitsch-2020-wscg-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Korpitsch-2020-wscg/", "__class": "Publication" }, { "id": "Groeller_V2_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87182", "title": "Visual Analytics in Radiation Therapy Planning", "date": "2020-05-15", "abstract": "Visual analytics concerns analytical reasoning supported by interactive visual interfaces. Radiation therapy is a complex treatment approach that requires careful planning. Visual analytics and visual computing are supportive in the entire radiation therapy workflow. After a brief survey on the workflow, concrete examples about radiation therapy planning for pelvic organs will be treated in detail. One example discusses visual analytics for the exploration of radio-therapy-induced bladder toxicity in a cohort study. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. In another example the pelvic organ variability in a cohort of radiotherapy patients is visualized. The application addresses the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. Research challenges and directions are sketched at the end of the talk.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "Mohn Medical Imaging and Visualization Centre (MMIV) Virtual Seminar", "location": "Bergen, Norway", "open_access": "yes", "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://mmiv.no/upcoming/mmiv-seminar-eduard-groeller/", "caption": null, "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V2_2020/", "__class": "Publication" }, { "id": "Mautner 2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/1119", "title": "Interactive 3D Storytelling for Planetary Exploration", "date": "2020-05-04", "abstract": "The Planetary Robotics 3D Viewer (PRo3D) is an interactive visualization tool thatallows for geological analyses of planetary surfaces. The primary goal is to supportgeologists at NASA and ESA in their mission to find signs of life on Mars by enablingthem to perform analyses on a high-resolution 3D surface model. While PRo3D facilitatesan exploratory workflow to gain new insights, there is a lack of support to communicatenew findings. In this thesis, we discuss the design and implementation of storytellingmechanisms into PRo3D that allow for an easy, fast, and interactive communicationof results. Moreover, we show how provenance information can be incorporated intostories, enabling geoscientists to present how they arrived at a certain discovery orinterpretation. Provenance includes the individual steps in the analysis process thatlead to a given finding, supporting its verification and reproducibility. We present abroad overview about storytelling and provenance in visualization, and discuss the designspace of a provenance-based storytelling approach in the context of geological analysesas conducted in PRo3D. Finally, we present a prototype as a proof of concept based onthese deliberations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 434, "image_height": 249, "name": "Mautner 2020-image.JPG", "type": "image/jpeg", "size": 30292, "path": "Publication:Mautner 2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1567 ], "date_end": "2020-05-04", "date_start": "2019-09", "diploma_examina": "2020-06", "matrikelnr": "1127229", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 434, "image_height": 249, "name": "Mautner 2020-image.JPG", "type": "image/jpeg", "size": 30292, "path": "Publication:Mautner 2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Mautner 2020-Master Thesis.pdf", "type": "application/pdf", "size": 13991167, "path": "Publication:Mautner 2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Mautner 2020-Poster.pdf", "type": "application/pdf", "size": 4976703, "path": "Publication:Mautner 2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/Mautner 2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mautner 2020/", "__class": "Publication" }, { "id": "Panayotov", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/15053", "title": " A Visual Exploration Tool forTemporal Analysis of CustomerReviews", "date": "2020-05-04", "abstract": "This thesis explores textual review data and how it changes over time. The thesisis motivated by the constantly generated textual reviews. Review sites like Yelp andTripAdvisor are generating hundreds of thousands of reviews monthly. Analysing thisamount of data is impossible by simply reading every individual review. We look forways to answer questions that business analysts, business owners, and investors ask aboutcustomer review data. This thesis asks questions such as: Why do review scores andtopics change over time? What are the major topics people discuss? What are the typicalreasons why review scores suddenly increase or decrease? What are topics that invokepermanent or transient changes in a large collection of review scores?We created a tool called Review Watcher, which provides novel approaches to examineand analyse review changes over time. The tool aims to provide simple, easily accessibleinformation regarding temporal changes in a collection of restaurant reviews. The tooluses real data provided by Yelp. It employs graphical ways to indicate changes in reviewscores over different periods of time. The tool analyses the review scores over time, andit tries to explain changes in these scores based on the textual content of the reviews.The tool utilises automated text processing algorithms to highlight important and oftenused words in text corpora.We used a qualitative evaluation to determine how well the tool manages to answer theresearch questions. We completed a user study with experts in the field of economics.They shared the insights they gathered using Review Watcher and compared them totheir experiences working with other tools for customer satisfaction and review analysis.As a result of our research, we show that Review Watcher manages to provide betterinsight into what are major topics in a collection of textual reviews. In the thesis, we showthat Review Watcher is better suited to highlighting review changes occurring over timeand giving insights to why the changes occurred, compared to existing tools for reviewexploration. The tool is also proving capable of handling millions of textual reviews oftens of thousands of restaurants with acceptable loading times for the user. The userstudy also reveals some of the tool’s limitations and potential for future work, for examplein introducing improved categorisation functions and geographical information about restaurants.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 365, "image_height": 207, "name": "Panayotov-image.JPG", "type": "image/jpeg", "size": 14323, "path": "Publication:Panayotov", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1686 ], "co_supervisor": [ 1110 ], "date_end": "2020-05-04", "date_start": "2019-06", "diploma_examina": "2020-06", "doi": "10.34726/hss.2020.70281", "matrikelnr": "01643722", "open_access": "yes", "pages": "106", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [ "Information Visualization", "Business Intelligence", "Social Network Analysis" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 365, "image_height": 207, "name": "Panayotov-image.JPG", "type": "image/jpeg", "size": 14323, "path": "Publication:Panayotov", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Panayotov-Master Thesis.pdf", "type": "application/pdf", "size": 4730518, "path": "Publication:Panayotov", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Panayotov-Poster.pdf", "type": "application/pdf", "size": 683771, "path": "Publication:Panayotov", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/Panayotov-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Panayotov/", "__class": "Publication" }, { "id": "korpitsch-2020-cescg", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Optimising 3D Mesh Unfoldings with Additional Gluetabs using Simulated Annealing", "date": "2020-05-03", "abstract": "3D Mesh unfolding is a process of transforming a 3D mesh into one or several 2D planar patches. The technique is widely used to produce papercraft models, where 3D ob- jects can be reconstructed from printed paper or paper-like materials. Nonetheless, the reconstruction of such mod- els can be arduous. In this paper, we aim to unfold a 3D mesh into a single 2D patch and introduce Gluetabs as ad- ditional indicators and in order to give users extra space to apply glue for better reconstruction quality. To avoid unnecessary Gluetabs, we reduce their number, while still guaranteeing the stability of the constructed model. To achieve this, a minimum spanning tree (MST) is used to describe possible unfoldings, whereas simulated annealing optimisation is used to find an optimal unfolding without overlaps. We aim to unfold 3D triangular meshes into sin- gle 2D patches without applying shape distortions, while appropriately assigning a reasonable amount of Gluetabs. Moreover, we incorporate a visual indicator scheme as a post-process to guide users during the model reconstruc- tion process. Our quantitative evaluation suggests that the proposed approach produces fast results for meshes under 400 faces.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 382, "image_height": 268, "name": "korpitsch-2020-cescg-image.png", "type": "image/png", "size": 95348, "path": "Publication:korpitsch-2020-cescg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1697, 1464 ], "booktitle": "CESCG ", "number": "TR-193-02-2020-2", "research_areas": [ "Fabrication" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 382, "image_height": 268, "name": "korpitsch-2020-cescg-image.png", "type": "image/png", "size": 95348, "path": "Publication:korpitsch-2020-cescg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-image:thumb{{size}}.png" }, { "description": "This paper has been selected for the Best Paper Award at CESCG 2020.", "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "korpitsch-2020-cescg-paper.pdf", "type": "application/pdf", "size": 13734147, "path": "Publication:korpitsch-2020-cescg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/korpitsch-2020-cescg-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/korpitsch-2020-cescg/", "__class": "Publication" }, { "id": "luksch_2020", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/58258", "title": "Real-Time Approximation of Photometric Polygonal Lights", "date": "2020-05-01", "abstract": "We present a real-time rendering technique for photometric polygonal lights. Our method uses a numerical integration technique based on a triangulation to calculate noise-free diffuse shading. We include a dynamic point in the triangulation that provides a continuous near-field illumination resembling the shape of the light emitter and its characteristics. We evaluate the accuracy of our approach with a diverse selection of photometric measurement data sets in a comprehensive benchmark framework. Furthermore, we provide an extension for specular reflection on surfaces with arbitrary roughness that facilitates the use of existing real-time shading techniques. Our technique is easy to integrate into real-time rendering systems and extends the range of possible applications with photometric area lights.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1621, "image_height": 343, "name": "luksch_2020-image.jpg", "type": "image/jpeg", "size": 71419, "path": "Publication:luksch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 659, 1377, 193 ], "cfp": { "name": "I3D 2020.pdf", "type": "application/pdf", "error": "0", "size": "128401", "orig_name": "I3D 2020.pdf", "ext": "pdf" }, "date_from": "2020-09-14", "date_to": "2020-09-18", "doi": "10.1145/3384537", "event": "ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games", "issn": "2577-6193", "journal": "Proceedings of the ACM on Computer Graphics and Interactive Techniques", "lecturer": [ 659 ], "location": "online", "number": "1", "open_access": "yes", "pages_from": "4.1", "pages_to": "4.18", "volume": "3", "research_areas": [ "Rendering" ], "keywords": [ "area lights", "photometric lights", "real-time rendering" ], "weblinks": [ { "href": "https://doi.org/10.1145/3384537", "caption": null, "description": null, "main_file": 0 }, { "href": "http://download.vrvis.at/acquisition/HILITE/60421ab2-455e-42e4-8f22-ecdb009e9829/I3D2020_PhotometricAreaLights_Final.mp4", "caption": "Video", "description": "Video", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1621, "image_height": 343, "name": "luksch_2020-image.jpg", "type": "image/jpeg", "size": 71419, "path": "Publication:luksch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "luksch_2020-Paper.pdf", "type": "application/pdf", "size": 6754960, "path": "Publication:luksch_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/luksch_2020-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "rend", "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/luksch_2020/", "__class": "Publication" }, { "id": "raidou_visgap2020", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58269", "title": "Lessons Learnt from Developing Visual Analytics Applications for Adaptive Prostate Cancer Radiotherapy", "date": "2020-05", "abstract": "In radiotherapy (RT), changes in patient anatomy throughout the treatment period might lead to deviations between planned\nand delivered dose, resulting in inadequate tumor coverage and/or overradiation of healthy tissues. Adapting the treatment to\naccount for anatomical changes is anticipated to enable higher precision and less toxicity to healthy tissues. Corresponding\ntools for the in-depth exploration and analysis of available clinical cohort data were not available before our work. In this\npaper, we discuss our on-going process of introducing visual analytics to the domain of adaptive RT for prostate cancer. This\nhas been done through the design of three visual analytics applications, built for clinical researchers working on the deployment\nof robust RT treatment strategies. We focus on describing our iterative design process, and we discuss the lessons learnt from\nour fruitful collaboration with clinical domain experts and industry, interested in integrating our prototypes into their workflow.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1733, 1366, 1444, 1568, 1569, 166, 1445 ], "booktitle": "The Gap between Visualization Research and Visualization Software (VisGap) (2020)", "cfp": { "name": "VisGap Workshop 2020.pdf", "type": "application/pdf", "error": "0", "size": "183556", "orig_name": "VisGap Workshop 2020.pdf", "ext": "pdf" }, "event": "EGEV2020 - VisGap Workshop", "lecturer": [ 1410 ], "open_access": "yes", "pages_from": "1", "pages_to": "8", "research_areas": [ "InfoVis", "MedVis" ], "keywords": [ "Visual Analytics", "Life and Medical Sciences" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1837, "preview_image_height": 998, "name": "raidou_visgap2020-paper.pdf", "type": "application/pdf", "size": 2068564, "path": "Publication:raidou_visgap2020", "preview_name": "raidou_visgap2020-paper:preview.PNG", "preview_type": "image/png", "preview_size": 87558, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/raidou_visgap2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/raidou_visgap2020-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_visgap2020/", "__class": "Publication" }, { "id": "tatzgern-2020-sst", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58270", "title": "Stochastic Substitute Trees for Real-Time Global Illumination", "date": "2020-05", "abstract": "With the introduction of hardware-supported ray tracing and deep learning for denoising, computer graphics has made a considerable step toward real-time global illumination. In this work, we present an alternative global illumination method: The stochastic substitute tree (SST), a hierarchical structure inspired by lightcuts with light probability distributions as inner nodes. Our approach distributes virtual point lights (VPLs) in every frame and efficiently constructs the SST over those lights by clustering according to Morton codes. Global illumination is approximated by sampling the SST and considers the BRDF at the hit location as well as the SST nodes’ intensities for importance sampling directly from inner nodes of the tree. To remove the introduced Monte Carlo noise, we use a recurrent autoencoder. In combination with temporal filtering, we deliver real-time global illumination for complex scenes with challenging light distributions.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 449, "preview_image_height": 270, "name": "tatzgern-2020-sst-.png", "type": "image/png", "size": null, "path": "Publication:tatzgern-2020-sst", "preview_name": "tatzgern-2020-sst-:preview.png", "preview_type": "image/png", "preview_size": 152699, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/tatzgern-2020-sst/tatzgern-2020-sst-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/tatzgern-2020-sst/tatzgern-2020-sst-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1762, 1763, 1650, 1662 ], "booktitle": "Symposium on Interactive 3D Graphics and Games", "cfp": { "name": "I3D 2020.pdf", "type": "application/pdf", "error": "0", "size": "1135142", "orig_name": "I3D 2020.pdf", "ext": "pdf" }, "event": "I3D ’20", "first_published": "2020-05", "lecturer": [ 1650 ], "pages_from": "1", "pages_to": "9", "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [ { "href": "https://dl.acm.org/doi/10.1145/3384382.3384521", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 449, "preview_image_height": 270, "name": "tatzgern-2020-sst-.png", "type": "image/png", "size": null, "path": "Publication:tatzgern-2020-sst", "preview_name": "tatzgern-2020-sst-:preview.png", "preview_type": "image/png", "preview_size": 152699, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/tatzgern-2020-sst/tatzgern-2020-sst-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/tatzgern-2020-sst/tatzgern-2020-sst-:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/tatzgern-2020-sst/", "__class": "Publication" }, { "id": "schuetz-2020-PPC", "type_id": "journalpaper", "tu_id": 291874, "repositum_id": "20.500.12708/58262", "title": "Progressive Real-Time Rendering of One Billion Points Without Hierarchical Acceleration Structures", "date": "2020-05", "abstract": "Research in rendering large point clouds traditionally focused on the generation and use of hierarchical acceleration structures that allow systems to load and render the smallest fraction of the data with the largest impact on the output. The generation of these structures is slow and time consuming, however, and therefore ill-suited for tasks such as quickly looking at scan data stored in widely used unstructured file formats, or to immediately display the results of point-cloud processing tasks.\n\n \nWe propose a progressive method that is capable of rendering any point cloud that fits in GPU memory in real time, without the need to generate hierarchical acceleration structures in advance. Our method supports data sets with a large amount of attributes per point, achieves a load performance of up to 100 million points per second, displays already loaded data in real time while remaining data is still being loaded, and is capable of rendering up to one billion points using an on-the-fly generated shuffled vertex buffer as its data structure, instead of slow-to-generate hierarchical structures. Shuffling is done during loading in order to allow efficiently filling holes with random subsets, which leads to a higher quality convergence behavior. ", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4061, "image_height": 1183, "name": "schuetz-2020-PPC-.jpg", "type": "image/jpeg", "size": 376597, "path": "Publication:schuetz-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1116, 1700, 1701, 193 ], "booktitle": "EUROGRAPHICS", "cfp": { "name": "EG_2020_call_for_papers.pdf", "type": "application/pdf", "error": "0", "size": "268041", "orig_name": "EG_2020_call_for_papers.pdf", "ext": "pdf" }, "date_from": "2020-05-25", "date_to": "2020-05-29", "doi": "10.1111/cgf.13911", "event": "EUROGRAPHICS 2020", "first_published": "2020-07-13", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1116 ], "location": "Norköpping, Sweden", "number": "2", "pages": "14", "pages_from": "51", "pages_to": "64", "publisher": "John Wiley & Sons Ltd.", "volume": "39", "research_areas": [ "Rendering" ], "keywords": [ "point-based rendering" ], "weblinks": [ { "href": "https://github.com/m-schuetz/skye", "caption": "Source Code", "description": null, "main_file": 0 }, { "href": "https://www.youtube.com/watch?v=6_ivIcynok8", "caption": "Video", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 4061, "image_height": 1183, "name": "schuetz-2020-PPC-.jpg", "type": "image/jpeg", "size": 376597, "path": "Publication:schuetz-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "schuetz-2020-PPC-paper.pdf", "type": "application/pdf", "size": 27594913, "path": "Publication:schuetz-2020-PPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/schuetz-2020-PPC-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "Superhumans" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/", "__class": "Publication" }, { "id": "unterguggenberger-2020-fmvr", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58271", "title": "Fast Multi-View Rendering for Real-Time Applications", "date": "2020-05", "abstract": "Efficient rendering of multiple views can be a critical performance factor for real-time rendering applications. Generating more than one view multiplies the amount of rendered geometry, which can cause a huge performance impact. Minimizing that impact has been a target of previous research and GPU manufacturers, who have started to equip devices with dedicated acceleration units. However, vendor-specific acceleration is not the only option to increase multi-view rendering (MVR) performance. Available graphics API features, shader stages and optimizations can be exploited for improved MVR performance, while generally offering more versatile pipeline configurations, including the preservation of custom tessellation and geometry shaders. In this paper, we present an exhaustive evaluation of MVR pipelines available on modern GPUs. We provide a detailed analysis of previous\ntechniques, hardware-accelerated MVR and propose a novel method, leading to the creation of an MVR catalogue. Our analyses cover three distinct applications to help gain clarity on overall MVR performance characteristics. Our interpretation of the observed results provides a guideline for selecting the most appropriate one for various use cases on different GPU architectures.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 917, "image_height": 687, "name": "unterguggenberger-2020-fmvr-image.png", "type": "image/png", "size": 62276, "path": "Publication:unterguggenberger-2020-fmvr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 848, 1650, 1662, 202, 193 ], "booktitle": "Eurographics Symposium on Parallel Graphics and Visualization", "cfp": { "name": "Call for Papers – EGPGV 2020.pdf", "type": "application/pdf", "error": "0", "size": "348754", "orig_name": "Call for Papers – EGPGV 2020.pdf", "ext": "pdf" }, "date_from": "2020-05-25", "date_to": "2020-05-25", "doi": "10.2312/pgv.20201071", "editor": "Frey, Steffen and Huang, Jian and Sadlo, Filip", "event": "EGPGV 2020", "isbn": "978-3-03868-107-6", "lecturer": [ 848 ], "location": "online", "open_access": "yes", "organization": "Eurographics", "pages_from": "13", "pages_to": "23", "research_areas": [ "Rendering" ], "keywords": [ "Real-Time Rendering", "Rasterization", "Multi-View", "OVR_multiview", "Geometry Shader", "Evaluation" ], "weblinks": [ { "href": "https://diglib.eg.org/handle/10.2312/pgv20201071", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 917, "image_height": 687, "name": "unterguggenberger-2020-fmvr-image.png", "type": "image/png", "size": 62276, "path": "Publication:unterguggenberger-2020-fmvr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-image:thumb{{size}}.png" }, { "description": "Fast Multi-View Rendering for Real-Time Applications", "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "unterguggenberger-2020-fmvr-paper.pdf", "type": "application/pdf", "size": 300803, "path": "Publication:unterguggenberger-2020-fmvr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-paper:thumb{{size}}.png" }, { "description": "Slides used for the talk", "filetitle": "slides", "main_file": false, "use_in_gallery": false, "access": "public", "name": "unterguggenberger-2020-fmvr-slides.pdf", "type": "application/pdf", "size": 4201932, "path": "Publication:unterguggenberger-2020-fmvr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/unterguggenberger-2020-fmvr-slides:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/unterguggenberger-2020-fmvr/", "__class": "Publication" }, { "id": "Mirzaei_Mohammadreza_2020-EVR", "type_id": "journalpaper", "tu_id": 291029, "repositum_id": "20.500.12708/140902", "title": "EarVR: Using Ear Haptics in Virtual Reality for Deaf and Hard-of-Hearing People", "date": "2020-05", "abstract": "Virtual Reality (VR) has a great potential to improve skills of Deaf and Hard-of-Hearing (DHH) people. Most VR applications and devices are designed for persons without hearing problems. Therefore, DHH persons have many limitations when using VR. Adding special features in a VR environment, such as subtitles, or haptic devices will help them. Previously, it was necessary to design a special VR environment for DHH persons. We introduce and evaluate a new prototype called \"EarVR\" that can be mounted on any desktop or mobile VR Head-Mounted Display (HMD). EarVR analyzes 3D sounds in a VR environment and locates the direction of the sound source that is closest to a user. It notifies the user about the sound direction using two vibro-motors placed on the user's ears. EarVR helps DHH persons to complete sound-based VR tasks in any VR application with 3D audio and a mute option for background music. Therefore, DHH persons can use all VR applications with 3D audio, not only those applications designed for them. Our user study shows that DHH participants were able to complete a simple VR task significantly faster with EarVR than without. The completion time of DHH participants was very close to participants without hearing problems. Also, it shows that DHH participants were able to finish a complex VR task with EarVR, while without it, they could not finish the task even once. Finally, our qualitative and quantitative evaluation among DHH participants indicates that they preferred to use EarVR and it encouraged them to use VR technology more.", "authors_et_al": false, "substitute": null, "main_image": { "description": "EarVR", "filetitle": "EarVR", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1110, "image_height": 602, "name": "Mirzaei_Mohammadreza_2020-EVR-EarVR.jpg", "type": "image/jpeg", "size": 499544, "path": "Publication:Mirzaei_Mohammadreza_2020-EVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mirzaei_Mohammadreza_2020-EVR/Mirzaei_Mohammadreza_2020-EVR-EarVR.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mirzaei_Mohammadreza_2020-EVR/Mirzaei_Mohammadreza_2020-EVR-EarVR:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1803, 1720, 378 ], "cfp": { "name": "cfp2020.pdf", "type": "application/pdf", "error": "0", "size": "516819", "orig_name": "cfp2020.pdf", "ext": "pdf" }, "date_from": "2020-03-22", "date_to": "2020-03-26", "doi": "10.1109/TVCG.2020.2973441", "event": "IEEE VR 2021", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 378 ], "number": "05", "open_access": "no", "pages_from": "2084", "pages_to": "2093", "volume": "26", "research_areas": [ "VR" ], "keywords": [ "Handicapped Aids", "Haptic Interfaces", "Helmet Mounted Displays", "Virtual Reality", "3 D Sounds", "3 D Audio", "Deaf And Hard Of Hearing People", "Head Mounted Display", "VR Application", "Ear VR", "VR Technology", "Haptic Devices", "DHH Persons", "Hearing Problems", "VR Apps." ], "weblinks": [ { "href": "https://www.computer.org/csdl/journal/tg/2020/05/08998298/1hrXce2Kmhq", "caption": "TVCG", "description": null, "main_file": 1 } ], "files": [ { "description": "EarVR", "filetitle": "EarVR", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1110, "image_height": 602, "name": "Mirzaei_Mohammadreza_2020-EVR-EarVR.jpg", "type": "image/jpeg", "size": 499544, "path": "Publication:Mirzaei_Mohammadreza_2020-EVR", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mirzaei_Mohammadreza_2020-EVR/Mirzaei_Mohammadreza_2020-EVR-EarVR.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mirzaei_Mohammadreza_2020-EVR/Mirzaei_Mohammadreza_2020-EVR-EarVR:thumb{{size}}.png" } ], "projects_workgroups": [ "vr" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mirzaei_Mohammadreza_2020-EVR/", "__class": "Publication" }, { "id": "Kovacs_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "VR Bridges: An Approach to Simulating Uneven Surfaces in VR", "date": "2020-04-30", "abstract": "Virtual reality (VR) promises boundless potential for experiences. Yet, due to technical restrictions, current VR experiences are often limited in many ways and incomparable to their real-world counterparts. Walkable smooth uneven surfaces are inherent to reality but lacking in VR. At the same time, VR enables the alteration and manipulation of perception, o˙ering tools for reshaping the experience. In this thesis, we explore the possibility of simulating walkable smooth uneven surfaces in VR via a multi-sensory stimulation approach. We examine human height and slant perception and incorporate our findings into a multi-modal approach by combining visual manipulations, haptic and vibrotactile stimuli.\nOur approach is realized by constructing physical bridge props and creating a complex software application to introduce multi-sensory stimuli to the user. The simulation is evaluated in two user studies, each focusing on one of two di˙erently shaped physical bridge props. In the studies, we evaluate the feasibility of a flat and an upward curved prop for the simulation of di˙erent virtual surface heights. The data collected during the studies is subjected to a qualitative and quantitative analysis.\nOur results suggest that the use of a curved prop enables the convincing simulation of significantly higher uneven surfaces than the actual height of the prop. The haptic feedback of the curved surface and the proprioceptive cues of actual vertical traversal facilitate user provided height and slant estimations to be closer to the values suggested by the visual cues. The use of a flat prop is less realistic and leads to height and slant underestimations, despite the simulated visual height and slant cues. However, a flat surface might be still used to simulate indentations and protrusions with smaller height di˙erences.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 348, "image_height": 181, "name": "Kovacs_2020-Image.JPG", "type": "image/jpeg", "size": 22461, "path": "Publication:Kovacs_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1487 ], "co_supervisor": [ 1712 ], "date_end": "2020-04-30", "date_start": "2019-10-20", "diploma_examina": "2020-04-30", "matrikelnr": "01227520", "open_access": "yes", "supervisor": [ 378 ], "research_areas": [ "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 348, "image_height": 181, "name": "Kovacs_2020-Image.JPG", "type": "image/jpeg", "size": 22461, "path": "Publication:Kovacs_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Kovacs_2020-Master Thesis.pdf", "type": "application/pdf", "size": 7768413, "path": "Publication:Kovacs_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/Kovacs_2020-Master Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vr" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Kovacs_2020/", "__class": "Publication" }, { "id": "Unger2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/1114", "title": "Interactive Visual Exploration ofLarge Bipartite Graphs usingFirework Plots", "date": "2020-04-30", "abstract": "In this thesis, we introduce a web-based interactive exploration interface for a broadaudience to investigate large, weighted, bipartite graphs. The motivation of this workis based on theMedia Transparency Databasewhich arises from an Austrian law thatcompels legal entities to announce their advertisement spendings to media organizationsand meets the specified characteristics.Most current interactive exploration tools use complex visualizations because they weredeveloped for domain experts. As the Media Transparency Database is of potentialinterest to a broad audience, we provide a framework not just for domain experts butalso for inexperienced users.Therefore, we conducted systematic benchmarks to compare state-of-the-art web-basedrendering techniques. Furthermore, we compared the performance of different librariesto determine the most efficient rendering solution and current limitations of web-basedrendering.We introduce the concept of Firework Plots, which aims to provide a common visualizationthat scales well with the size of the data. Our visualization concept is based on intuitivenode-link visualization in combination with multiple visualization and interaction concepts.Hierarchical aggregation is used to improve scalability. Constrained, layered, force-basedgraph layouts, as well as firework animations and seamless zoom, are used to allowinexperienced users to drill down the graph hierarchy and track nodes through thehierarchy. Moreover, visibility management is used to reduce clutter and improveperformance.Based on the insights of our web-based graph rendering analysis, we implementedour framework and the concept of Firework Plots. We show the usefulness of theimplementation by discussing different use cases and comparing it to related work.Moreover, we conducted multiple benchmarks to show the rendering performance and calculation times.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 430, "image_height": 275, "name": "Unger2020-image.JPG", "type": "image/jpeg", "size": 44075, "path": "Publication:Unger2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1530 ], "date_end": "2020-04-30", "date_start": "2019-04-01", "diploma_examina": "2020-05", "doi": "10.34726/hss.2020.66221", "matrikelnr": "01325652", "open_access": "yes", "pages": "104", "supervisor": [ 166, 1110 ], "research_areas": [ "IllVis" ], "keywords": [ "Node-Link Diagram", "Bipartite Projection" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/kunger/da-bipartite-node-link/?data=MTD-20123-20194_filtered_o31t", "caption": "Firework Plots Online", "description": "Firework plots showing the Media Transparency Database data 2012 to 2019 (without §31). ", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 430, "image_height": 275, "name": "Unger2020-image.JPG", "type": "image/jpeg", "size": 44075, "path": "Publication:Unger2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Unger2020-Master Thesis.pdf", "type": "application/pdf", "size": 18029327, "path": "Publication:Unger2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Unger2020-Poster.pdf", "type": "application/pdf", "size": 1727745, "path": "Publication:Unger2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Unger2020-video.mp4", "type": "video/mp4", "size": 30258086, "path": "Publication:Unger2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/Unger2020-video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Unger2020/", "__class": "Publication" }, { "id": "schindler2020", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Anatomical Entertainer: Physical Visualization in a Medical Context", "date": "2020-04-24", "abstract": "Visualizations are essential for anatomical education of the general public. Traditional\nvisualization methods focus on 2D and 3D information representations, either digital\nor printed, but visualizations also have a physical form. Physical visualization is a\nsubdomain of the traditional visualization domain, where the data is represented by\nmeans of a physical object. Physical visualizations have been reported to lead to greater information insights for the interacting user, but a lot of the fabrication methods to create physical visualizations of the anatomy are not accessible for the general public. In\nthis thesis, we present a workflow to ease the process of creating physical visualizations, made out of paper. The proposed workflow can be used to create two different types of anatomical visualizations. First, we generate 2D visualizations, examinable with color\nfilters that enhance the interactivity of the visualization. To encode multiple channels of information from the anatomical structures, a specific method of color blending is used, which enables the users to access the different anatomical structures selectively, without occlusion. That way the users explore the single layers of the printed visualizations using color filters. Second, 3D papercrafts are generated, which are also examinable with color filters. The anatomical model is unfolded on the paper sheet, can be printed and the user can assemble it and examine it under the color lenses, similarly to the 2D case. The papercrafts may be used as an educational toy in school teaching or for entertainment, since they are very easy to produce and to distribute. We present several 2D and 3D examples of the workflow of the Anatomical Entertainer on models for anatomical education.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1084, "image_height": 324, "name": "schindler2020-image.PNG", "type": "image/png", "size": 602230, "path": "Publication:schindler2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1760 ], "date_end": "2020-04-24", "date_start": "2019-09-01", "matrikelnr": "01627754", "supervisor": [ 1410 ], "research_areas": [ "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor thesis", "main_file": true, "use_in_gallery": true, "access": "public", "preview_image_width": 1084, "preview_image_height": 324, "name": "schindler2020-Bachelor thesis.pdf", "type": "application/pdf", "size": 10893906, "path": "Publication:schindler2020", "preview_name": "schindler2020-Bachelor thesis:preview.PNG", "preview_type": "image/png", "preview_size": 602230, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-Bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-Bachelor thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1084, "image_height": 324, "name": "schindler2020-image.PNG", "type": "image/png", "size": 602230, "path": "Publication:schindler2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/schindler2020-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/schindler2020/", "__class": "Publication" }, { "id": "Spelitz2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/1120", "title": "BrainGait: Gait Event Detection and Visualization for Robotic Rehabilitation", "date": "2020-04-21", "abstract": "Mobility impairment in adults is one of most prevalent types of disabilities in developed countries. Gait rehabilitation can be used to regain some or all motor functions, especially after a stroke. In recent years, robot-assisted gait training attracted increasing interest in rehabilitation facilities and scientific research. With this advent of robotic recovery comes the need to objectively measure the patient’s performance. Physiotherapists need essential information about the current status during training and how to improve the patient’s gait, presented in an easy to grasp and compact form. On the other hand, physicians rely on statistical measures in order to evaluate the patient’s progress throughout the therapy. This thesis discusses commonly used visualizations and statistics while proposing improvements and adaptations in the context of PerPedes, a novel robotic gait rehabilitation device. In order to measure the patient’s performance, a new algorithm for gait event detection was developed, based on force data from pressure plates. The following work demonstrates that standard algorithms fail with PerPedes, while the proposed solution can robustly handle highly distorted gait patterns, such as hemiplegic gait, foot drop, or walking backwards. The software application developed during this thesis provides feedback to the therapist and generates suggestions for gait improvement. Furthermore, gait statistics are inferred from each therapy session and collected in order to be used for future analysis and inter-patient comparison.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1713, "image_height": 1025, "name": "Spelitz2020-image.jpg", "type": "image/jpeg", "size": 430173, "path": "Publication:Spelitz2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1015 ], "date_end": "2020-04-21", "date_start": "2019-03", "diploma_examina": "2020-05", "doi": "10.34726/hss.2020.57203", "matrikelnr": "0925601", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "MedVis" ], "keywords": [ "Mobility rehabilitation", "Electroencephalography" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1713, "image_height": 1025, "name": "Spelitz2020-image.jpg", "type": "image/jpeg", "size": 430173, "path": "Publication:Spelitz2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Spelitz2020-Master Thesis.pdf", "type": "application/pdf", "size": 18131909, "path": "Publication:Spelitz2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": false, "use_in_gallery": true, "access": "public", "name": "Spelitz2020-Poster.pdf", "type": "application/pdf", "size": 2797037, "path": "Publication:Spelitz2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/Spelitz2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Spelitz2020/", "__class": "Publication" }, { "id": "brugger-2020-tsdpbr", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Test Scene Design for Physically Based Rendering", "date": "2020-04", "abstract": "Physically based rendering is a discipline in computer graphics which aims at reproducing certain light and material appearances that occur in the real world.\nComplex scenes can be difficult to compute for rendering algorithms.\nThe goal of this thesis is to create a comprehensive test database of scenes that treat different light setups in conjunction with diverse materials.\nA lot of research is focused on the development of new algorithms that can deal with difficult light conditions and materials efficiently.\nThis database should deliver a comprehensive foundation for evaluating existing and newly developed rendering techniques.\nA final evaluation will compare different results of different rendering algorithms for all scenes. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1780 ], "date_end": "2020-04", "date_start": "2019-10", "matrikelnr": "01527088", "supervisor": [ 193, 1128 ], "research_areas": [ "Rendering" ], "keywords": [ "Physically Based Rendering", "Database", "Verification", "Tests" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "brugger-2020-tsdpbr-thesis.pdf", "type": "application/pdf", "size": 55508619, "path": "Publication:brugger-2020-tsdpbr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tsdpbr/brugger-2020-tsdpbr-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tsdpbr/brugger-2020-tsdpbr-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend", "OpenData" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/brugger-2020-tsdpbr/", "__class": "Publication" }, { "id": "leimer_2020-cag", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141145", "title": "Pose to Seat: Automated design of body-supporting surfaces", "date": "2020-04", "abstract": "The design of functional seating furniture is a complicated process which often requires extensive manual design effort and empirical evaluation. We propose a computational design framework for pose-driven automated generation of body-supports which are optimized for comfort of sitting. Given a human body in a specified pose as input, our method computes an approximate pressure distribution that also takes frictional forces and body torques into consideration which serves as an objective measure of comfort. Utilizing this information to find out where the body needs to be supported in order to maintain comfort of sitting, our algorithm can create a supporting mesh suited for a person in that specific pose. This is done in an automated fitting process, using a template model capable of supporting a large variety of sitting poses. The results can be used directly or can be considered as a starting point for further interactive design.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 627, "image_height": 636, "name": "leimer_2020-cag-image.png", "type": "image/png", "size": 270901, "path": "Publication:leimer_2020-cag", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1019, 1422, 948, 844 ], "date_from": "2020-01-01", "date_to": "2020-01-01", "event": "Conference", "journal": "Computer Aided Geometric Design", "open_access": "yes", "pages_from": "1", "pages_to": "1", "volume": "79", "research_areas": [ "Fabrication", "Geometry", "Modeling" ], "keywords": [ "pose estimation", "furniture", "computational design" ], "weblinks": [ { "href": "https://arxiv.org/pdf/2003.10435.pdf", "caption": "paper", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 627, "image_height": 636, "name": "leimer_2020-cag-image.png", "type": "image/png", "size": 270901, "path": "Publication:leimer_2020-cag", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "leimer_2020-cag-Paper.pdf", "type": "application/pdf", "size": 3539714, "path": "Publication:leimer_2020-cag", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/leimer_2020-cag-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "Superhumans", "MAKE-IT-FAB", "geo-materials" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/leimer_2020-cag/", "__class": "Publication" }, { "id": "gundacker-2020-wlm", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Wilangyman - Eine Google-Chrome Erweiterung die Wikipedia-Artikel um fremdsprachliche Inhalte ergänzt", "date": "2020-04", "abstract": "Wikipedia-Artikel unterscheiden sich in den unterschiedlichen Sprachversionen oft in\nStruktur und Inhalt. Manche Informationen sind nicht in allen Sprachen verfügbar.\nDas hat zur Folge, dass NutzerInnen wichtige Daten aus der Online Enzyklopädie\nentgehen, wenn sie sich auf eine Sprache beschränken. Ziel von Wilangyman ist es, diese\nInformationen zusammenzuführen und sie in übersichtlicher Art dem Nutzer oder der\nNutzerin zu präsentieren. Die Artikel werden mittels Natural Language Processing (NLP)\nverglichen und und anhand ihrer Ähnlichkeiten miteinander verknüpft. Korrespondierende\nPassagen mit zusätzlichem Informationsgehalt werden absatzweise dargestellt. Inhaltliche\nRedundanzen sollen dabei vermieden werden.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1649 ], "date_end": "2020-04", "date_start": "2019-04", "matrikelnr": "08908802", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "gundacker-2020-wlm-thesis.pdf", "type": "application/pdf", "size": 1436642, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/", "__class": "Publication" }, { "id": "hanko-2019-ani", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Higher Hand-Drawn Detail Quality using Convolutional Assistant", "date": "2020-04", "abstract": "The field of research in the use of neural networks to help artists or advance 2D animation\nis very underdeveloped. Most of the little research that is done does not even ask questions\nthat are relevant for animators but is done in a pure research mindset. We, however,\ntried to find a problem that would actually be relevant in the animation industry and\ncame up with the idea of enhancing the feature quality of poorly drawn features in 2D\nanimation. The basis for this idea is that, as a cost and time-saving measure, in 2d\nanimation features are often drawn in different levels of detail depending on the current\nfocus of the scene and other factors. The focus will thereby lie on the enhancement of\ncharacters’ eyes with the idea that other features could be done in a similar way in future\nwork. To achieve this quality enhancing we train the FUNIT network on a\nmanually created dataset consisting of crops of eyes from different characters in different\nquality with the goal that it will be able to consistently transform low-quality eye images\ninto high-quality eye images", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "hanko-2019-ani-teaser.jpg", "type": "image/jpeg", "size": 45990, "path": "Publication:hanko-2019-ani", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1744 ], "date_end": "2020-04", "date_start": "2019-10", "matrikelnr": "01625726", "supervisor": [ 1639, 193 ], "research_areas": [], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "hanko-2019-ani-teaser.jpg", "type": "image/jpeg", "size": 45990, "path": "Publication:hanko-2019-ani", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser:thumb{{size}}.png" } }, "projects_workgroups": [ "EVOCATION" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/", "__class": "Publication" }, { "id": "waldner-2020-tbg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141146", "title": "Interactive exploration of large time-dependent bipartite graphs", "date": "2020-04", "abstract": "Bipartite graphs are typically visualized using linked lists or matrices, but these visualizations neither scale well nor do they convey temporal development. We present a new interactive exploration interface for large, time-dependent bipartite graphs. We use two clustering techniques to build a hierarchical aggregation supporting different exploration strategies. Aggregated nodes and edges are visualized as linked lists with nested time series. We demonstrate two use cases: finding advertising expenses of public authorities following similar temporal patterns and comparing author-keyword co-occurrences across time. Through a user study, we show that linked lists with hierarchical aggregation lead to more insights than without.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Dynamic BicFlows with nested time series visualization per cluster per set.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1121, "image_height": 936, "name": "waldner-2020-tbg-teaser.png", "type": "image/png", "size": 250456, "path": "Publication:waldner-2020-tbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1110, 1378, 166 ], "doi": "https://doi.org/10.1016/j.cola.2020.100959", "journal": "Journal of Computer Languages", "volume": "57", "research_areas": [ "InfoVis", "NetVis" ], "keywords": [ "Information visualization", "Bipartite graphs", "Clustering", "Time series data", "Insight-based evaluation" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S2590118420300198", "caption": "paper", "description": "Open Access article at ScienceDirect", "main_file": 1 } ], "files": [ { "description": "Dynamic BicFlows with nested time series visualization per cluster per set.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1121, "image_height": 936, "name": "waldner-2020-tbg-teaser.png", "type": "image/png", "size": 250456, "path": "Publication:waldner-2020-tbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "deskollage" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/", "__class": "Publication" }, { "id": "reina-2020-mtv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141135", "title": "The moving target of visualization software for an increasingly complex world", "date": "2020-04", "abstract": "Visualization has evolved into a mature scientific field and it has also become widely accepted as a standard approach in diverse fields, including physics, life sciences, and business intelligence. However, despite its successful development, there are still many open research questions that require customized implementations in order to explore and establish concepts, and to perform experiments and take measurements. Many methods and tools have been developed and published but most are stand-alone prototypes and have not reached a mature state that can be used in a reliable manner by collaborating domain scientists or a wider audience. In this study, we discuss the challenges, solutions, and open research questions that affect the development of sophisticated, relevant, and novel scientific visualization solutions with minimum overheads. We summarize and discuss the results of a recent National Institute of Informatics Shonan seminar on these topics.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 301, "image_height": 121, "name": "reina-2020-mtv-teaser.jpg", "type": "image/jpeg", "size": 15741, "path": "Publication:reina-2020-mtv", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reina-2020-mtv/reina-2020-mtv-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reina-2020-mtv/reina-2020-mtv-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1750, 1751, 235, 231, 1110, 1752, 1248, 951, 1753, 1754, 166, 1249 ], "doi": "https://doi.org/10.1016/j.cag.2020.01.005", "journal": "Computers & Graphics", "pages_from": "12", "pages_to": "29", "volume": "87", "research_areas": [], "keywords": [ "Software engineering", "Visualization", "Visualization community", "Visualization research", "Visualization software" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849320300078", "caption": "paper", "description": "Online paper on ScienceDirect", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 301, "image_height": 121, "name": "reina-2020-mtv-teaser.jpg", "type": "image/jpeg", "size": 15741, "path": "Publication:reina-2020-mtv", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reina-2020-mtv/reina-2020-mtv-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reina-2020-mtv/reina-2020-mtv-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reina-2020-mtv/", "__class": "Publication" }, { "id": "Schrempf_2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": " Fantastic Voyage: An AugmentedReality Approach to AnatomicalEducation for the General Public", "date": "2020-03-05", "abstract": "The purpose of this master thesis is the development of a mobile, anatomical educationapplication for the general public, which shifts the passive, unthoughtful mobile deviceusage to a more active, teaching usage by utilizing macroscopic and regional anatomy. The new, immersive learning experience with interactive, Three Dimensional (3D), Aug-mented Reality (AR) anatomy models synchronizes the models in realtime with the user’sface. Individuals of the general public can digitally dissect their own facial anatomy tolearn geometrical, spatial, and textual anatomy features.Immanent features of the created learning process are self-directed anatomy learning,less cognitive load, a motivation-, attention-, concentration increase, longer preserved sat-isfaction, new anatomical knowledge, and better spatial abilities compared to traditionallearning. The high complexity of the human anatomy restricts the synchronized anatomymodels to the head. Notwithstanding, all human anatomy models can be viewed as TwoDimensional (2D) or AR 3D renderings, whereby only the head anatomy is synchronizedwith the user’s head. The answered research questions are “How can interactive AR be used in anatomicaleducation for the general public?” and “How much and what anatomy can be learned inwhich time with the developed application compared to state of the art works?”. HeadPose Estimation (HPE) links AR managed by the framework ARCore with 3D anatomymodels from Body Parts 3D (BP3D) and anatomy information from FoundationalModel of Anatomy (FMA) to educate the general public in anatomy. Recommended requirements from professional literature are fulfilled by the developed mobile application named ARnatomy, which is a jointed, anatomical, interactive learning experience. The development result has been evaluated in an informal study with eight participants, whichshowed that mobile AR can be used for the anatomical education of the general public.Seven of eight participants gained anatomical knowledge in a geometrical, spatial, and textual form.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 224, "image_height": 302, "name": "Schrempf_2020-image.PNG", "type": "image/png", "size": 164985, "path": "Publication:Schrempf_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1552 ], "date_end": "2020-03-05", "date_start": "2019-06-05", "diploma_examina": "2020-03-25", "matrikelnr": "00920136", "open_access": "yes", "supervisor": [ 166, 1410 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 224, "image_height": 302, "name": "Schrempf_2020-image.PNG", "type": "image/png", "size": 164985, "path": "Publication:Schrempf_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Schrempf_2020-Master Thesis.pdf", "type": "application/pdf", "size": 8899312, "path": "Publication:Schrempf_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Schrempf_2020-Poster.pdf", "type": "application/pdf", "size": 4760141, "path": "Publication:Schrempf_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/Schrempf_2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Schrempf_2020/", "__class": "Publication" }, { "id": "Vasylevska2020VRB", "type_id": "inproceedings", "tu_id": 292209, "repositum_id": null, "title": "VR Bridges: An Approach to Uneven Surfaces Simulation in VR ", "date": "2020-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1256, "image_height": 496, "name": "Vasylevska2020VRB-image.png", "type": "image/png", "size": 896522, "path": "Publication:Vasylevska2020VRB", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1712, 1487, 378 ], "booktitle": "Proceedings of IEEE Conference on Virtual Reality 2020", "cfp": { "name": "Call for Papers.html", "type": "text/html", "error": "0", "size": "134732", "orig_name": "Call for Papers.html", "ext": "html" }, "date_from": "2020-03-22", "date_to": "2020-03-26", "doi": "10.1109/VR46266.2020.00-45", "event": "IEEE Conference on Virtual Reality 2020", "lecturer": [ 1712 ], "location": "Atlanta, USA", "open_access": "yes", "pages_from": "388", "pages_to": "397", "publisher": "IEEE", "research_areas": [ "VR" ], "keywords": [ "Virtual Reality", "height perception", "haptics", "simulation", "vibration", "physical props " ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1256, "image_height": 496, "name": "Vasylevska2020VRB-image.png", "type": "image/png", "size": 896522, "path": "Publication:Vasylevska2020VRB", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-image:thumb{{size}}.png" }, { "description": "Author's copy of the publication", "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Vasylevska2020VRB-paper.pdf", "type": "application/pdf", "size": 2854687, "path": "Publication:Vasylevska2020VRB", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/Vasylevska2020VRB-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Vasylevska2020VRB/", "__class": "Publication" }, { "id": "kroesl-2020-XREye", "type_id": "otherreviewed", "tu_id": null, "repositum_id": null, "title": "XREye: Simulating Visual Impairments in Eye-Tracked XR ", "date": "2020-03", "abstract": "Many people suffer from visual impairments, which can be difficult for patients to describe and others to visualize. To aid in understanding what people with visual impairments experience, we demonstrate a set of medically informed simulations in eye-tracked XR of several common conditions that affect visual perception: refractive errors (myopia, hyperopia, and presbyopia), cornea disease, and age-related macular degeneration (wet and dry).", "authors_et_al": false, "substitute": null, "main_image": { "description": "live demo in mozilla social hubs room", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 561, "image_height": 414, "name": "kroesl-2020-XREye-image.png", "type": "image/png", "size": 327573, "path": "Publication:kroesl-2020-XREye", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1030, 1633, 1636, 1635, 1634, 193 ], "booktitle": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)", "location": "(Atlanta) online", "open_access": "yes", "publisher": "IEEE", "research_areas": [ "Perception", "Rendering", "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": "extended abstract of the research demo", "filetitle": "extended abstract", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kroesl-2020-XREye-extended abstract.pdf", "type": "application/pdf", "size": 121548, "path": "Publication:kroesl-2020-XREye", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-extended abstract.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-extended abstract:thumb{{size}}.png" }, { "description": "live demo in mozilla social hubs room", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 561, "image_height": 414, "name": "kroesl-2020-XREye-image.png", "type": "image/png", "size": 327573, "path": "Publication:kroesl-2020-XREye", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kroesl-2020-XREye-poster.pdf", "type": "application/pdf", "size": 3057039, "path": "Publication:kroesl-2020-XREye", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kroesl-2020-XREye-video.mp4", "type": "video/mp4", "size": 8756217, "path": "Publication:kroesl-2020-XREye", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/kroesl-2020-XREye-video:video.mp4" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kroesl-2020-XREye/", "__class": "Publication" }, { "id": "reimer-2020-CBG", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "The Influence of Full-Body Representation on Translation and CurvatureGain", "date": "2020-03", "abstract": "Redirected Walking (RDW) techniques allow users to navigate immersive virtual environments much larger than the available tracking space by natural walking. Whereas several approaches exist, numerous RDW techniques operate by applying gains of different types to the user’s viewport. These gains must remain undetected by the user in order for a RDW technique to support plausible navigation within a virtual environment. The present paper explores the relationship between detection thresholds of redirection gains and the presence of a self-avatar within the virtual environment. In four psychophysical experiments we estimated the thresholds of curvature and translation gain with and without a virtual body. The goal was to evaluate whether a full-body representation has an impact on the detection thresholds of these gains. The results indicate that although the presence of a virtual body does not significantly affect the detectability of these gains, it supports users with the illusion of easier detection. We discuss the possibility of a future combination of full-body representations and redirected walking and if these findings influence the implementation of large virtual environments with immersive virtual body representation.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "banner_paper", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1772, "image_height": 591, "name": "reimer-2020-CBG-banner_paper.jpg", "type": "image/jpeg", "size": 165848, "path": "Publication:reimer-2020-CBG", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reimer-2020-CBG/reimer-2020-CBG-banner_paper.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reimer-2020-CBG/reimer-2020-CBG-banner_paper:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1832, 1880, 378, 452 ], "booktitle": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstractsand Workshops (VRW)", "cfp": { "name": "VHCIE@IEEEVR2020 - Submission.pdf", "type": "application/pdf", "error": "0", "size": "40118", "orig_name": "VHCIE@IEEEVR2020 - Submission.pdf", "ext": "pdf" }, "doi": "10.1109/VRW50115.2020.00032", "event": "IEEEVR 2020", "isbn": "978-1-7281-6532-5", "issn": "978-1-7281-6533-2", "location": "Atlanta, US", "pages": "154-159", "pages_from": "154", "pages_to": "159", "publisher": "IEEE", "research_areas": [ "VR" ], "keywords": [ "redirected walking", "body representation", "curvature gain", "translation gain" ], "weblinks": [ { "href": "https://ieeexplore.ieee.org/document/9090671", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "banner_paper", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1772, "image_height": 591, "name": "reimer-2020-CBG-banner_paper.jpg", "type": "image/jpeg", "size": 165848, "path": "Publication:reimer-2020-CBG", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reimer-2020-CBG/reimer-2020-CBG-banner_paper.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/reimer-2020-CBG/reimer-2020-CBG-banner_paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vr" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/reimer-2020-CBG/", "__class": "Publication" }, { "id": "breitenecker-2020-bct", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "BibTeX Consitency Tool - Web Service for Consistency Checks of BibTeX Files", "date": "2020-03", "abstract": "This thesis presents cleanBibTeX, an application that can detect and correct inconsistencies in BibTEX files. BibTEX is a popular reference management system for LATEX. Unfortunately, when BibTEX files grow with respect to size or come from different sources, they can get inconsistent. For example, titles may have an inconsistent capitalization style, or the bibliography includes abbreviated author names. For a user, it can take a\nlong time to detect such inconsistencies manually. cleanBibTeX allows the user to clean up a bibliography with a few mouseclicks.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1685 ], "date_end": "2020-04", "date_start": "2019-08", "matrikelnr": "01346716", "supervisor": [ 1110 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "breitenecker-2020-bct-bachelor thesis.pdf", "type": "application/pdf", "size": 757926, "path": "Publication:breitenecker-2020-bct", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/breitenecker-2020-bct/breitenecker-2020-bct-bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/breitenecker-2020-bct/breitenecker-2020-bct-bachelor thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/breitenecker-2020-bct/", "__class": "Publication" }, { "id": "wiesinger_2020_odpr", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "An Open Database for Physically Based Rendering", "date": "2020-03", "abstract": "The propagation of light and its interaction with matter can be simulated using mathematical models,\nmost commonly Bidirectional Reflectance Distribution Functions (BRDFs).\nHowever, the creation of physically accurate BRDFs and their verification can be challenging.\nIn order to be able to test and verify physically-based rendering algorithms, various methods have been researched.\nHowever, they are rarely used by the community.\nOne key to the verification of rendering algorithms is to provide test-methods and test-data.\nAnother key is to motivate the community to actually use them and run more tests.\nThis thesis focuses on the latter. For this purpose, the author designed a web-application called “Open Database for Physically-based Rendering (ODPR)”,\nwhere test-scenes of different types and from different studies will be merged into one publicly available place.\nA prototype for ODPR was implemented.\nThe web-application uses community-driven design-patterns similar to StackExchange-sites,\nand allows scientists to register and upload test-scenes.\nThe idea is, that ODPR will be built up and maintained with the help of the community,\nby providing free downloads of test-scenes and additional privileges to registered users. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1614 ], "co_supervisor": [ 1128 ], "date_end": "2020-03", "date_start": "2018-03", "matrikelnr": "01429087", "supervisor": [ 193 ], "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wiesinger_2020_odpr-thesis.pdf", "type": "application/pdf", "size": 2109257, "path": "Publication:wiesinger_2020_odpr", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wiesinger_2020_odpr/wiesinger_2020_odpr-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wiesinger_2020_odpr/wiesinger_2020_odpr-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend", "OpenData" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wiesinger_2020_odpr/", "__class": "Publication" }, { "id": "djuric-2020-wvo", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Web-based visualization of classification and community detection in medical data", "date": "2020-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1198, "preview_image_height": 568, "name": "djuric-2020-wvo-.pdf", "type": "application/pdf", "size": 6761303, "path": "Publication:djuric-2020-wvo", "preview_name": "djuric-2020-wvo-:preview.jpg", "preview_type": "image/jpeg", "preview_size": 57582, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/djuric-2020-wvo/djuric-2020-wvo-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/djuric-2020-wvo/djuric-2020-wvo-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5336 ], "date_end": "2020", "date_start": "2019", "matrikelnr": "01227873", "supervisor": [ 1410 ], "research_areas": [ "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1198, "preview_image_height": 568, "name": "djuric-2020-wvo-.pdf", "type": "application/pdf", "size": 6761303, "path": "Publication:djuric-2020-wvo", "preview_name": "djuric-2020-wvo-:preview.jpg", "preview_type": "image/jpeg", "preview_size": 57582, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/djuric-2020-wvo/djuric-2020-wvo-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/djuric-2020-wvo/djuric-2020-wvo-:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/djuric-2020-wvo/", "__class": "Publication" }, { "id": "Swoboda2020", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Visualisation and Interaction Techniques for the Exploration of the Fruit Fly’s Neural Structure", "date": "2020-02-27", "abstract": "In their studies of the brain of the common fruit fly Drosophila melanogaster, neuro-biologists investigate neural connectivity with the goal to discover how complex be-haviour is generated. Gaining information on potential connectivity between neurons is an essential step in their workflow. This thesis presents a way to compute and visualise such potential connectivity information from segmented neurons. It shortens the tedious month-long search for potential connectivity down to a few minutes.\nOverlaps of arborisations of two or more neurons indicate a potential anatomical connection, and thus a potential functional connection. The computation of this data starts from neuron meshes. The meshes—segmented from confocal light-microscopy images of the fruit fly—are intersected to find overlapping areas, i.e. areas of potential anatomical connectivity. This information can then help to discover actual functional connectivity in a neural circuit.\nAnalysing higher order overlaps, i.e. intersections of more than two arborisations of segmented neuron data in the same location, poses new challenges. The visualisation in 2D sections or 3D is impeded by visual clutter and occlusion. Computation of relevant volumetric information becomes difficult for higher order overlaps, because the number of possible overlaps increases exponentially with the number of arborisations. This makes the pre-computation for all possible combinations infeasible. Previous tools have thus been restricted to the quantification and visualisation of pairwise overlaps.\nThe thesis presents a novel solution addressing these issues for higher order over-laps. A novel abstracting design is coupled with a modern approach for on-demand GPU computations. Our tool calculates for the first time volumetric information of higher order overlaps on the GPU using A-buffers. The thesis addresses the visual com-plexity of the data with the implementation of an innovative novel design created by the graphics designer Judith Moosburner. We realised this design using non-photorealistic rendering techniques and perspicuous user interfaces, including interactive glyphs and linked views on quantitative overlap information. To complement the neuroscientists’ workflows the resulting interactive tool has been integrated into BrainGazer, a software tool for advanced visualisation and exploration of neural images and circuit data. Qual-itative evaluation with neuroscientists and non-expert users demonstrated the utility and usability of the tool.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 329, "image_height": 311, "name": "Swoboda2020-image.JPG", "type": "image/jpeg", "size": 22737, "path": "Publication:Swoboda2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1358 ], "co_supervisor": [ 231 ], "date_end": "2020-02-27", "date_start": "2019-09-20", "diploma_examina": "2020-05", "matrikelnr": "0425828", "open_access": "yes", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 329, "image_height": 311, "name": "Swoboda2020-image.JPG", "type": "image/jpeg", "size": 22737, "path": "Publication:Swoboda2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Swoboda2020-Master Thesis.pdf", "type": "application/pdf", "size": 14837665, "path": "Publication:Swoboda2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Swoboda2020-Poster.pdf", "type": "application/pdf", "size": 2513316, "path": "Publication:Swoboda2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/Swoboda2020-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Swoboda2020/", "__class": "Publication" }, { "id": "kouril-2020-hyperlabels", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "HyperLabels: Browsing of Dense and Hierarchical Molecular 3D Models", "date": "2020-02-24", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 255, "image_height": 189, "name": "kouril-2020-hyperlabels-image.JPG", "type": "image/jpeg", "size": 25538, "path": "Publication:kouril-2020-hyperlabels", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1383, 960, 1248, 1746, 166, 171 ], "cfp": { "name": "Gmail - IEEE VIS 2020 - Call for Participation_ Papers; Workshops; Doctoral Colloquium.pdf", "type": "application/pdf", "error": "0", "size": "124288", "orig_name": "Gmail - IEEE VIS 2020 - Call for Participation_ Papers; Workshops; Doctoral Colloquium.pdf", "ext": "pdf" }, "date_from": "2020-02-24", "date_to": "2020-02-24", "doi": "10.1109/TVCG.2020.2975583", "event": "IEEE Vis 2020", "first_published": "2020-02-24", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1383 ], "note": "to appear", "open_access": "yes", "pages_from": "1", "pages_to": "12", "volume": "1", "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 255, "image_height": 189, "name": "kouril-2020-hyperlabels-image.JPG", "type": "image/jpeg", "size": 25538, "path": "Publication:kouril-2020-hyperlabels", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "kouril-2020-hyperlabels-Paper.pdf", "type": "application/pdf", "size": 17304362, "path": "Publication:kouril-2020-hyperlabels", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/kouril-2020-hyperlabels-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/kouril-2020-hyperlabels/", "__class": "Publication" }, { "id": "houska-2020-IPGM", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Improved Persistent Grid Mapping", "date": "2020-02-07", "abstract": "We propose a novel heightmap-based terrain rendering algorithm that enhances the Persistent Grid Mapping (PGM) method. As in the underlying method, we cache a regular triangulated grid in video memory and use the GPU to project the mesh onto the ground plane each frame anew. Each vertex in the grid is then displaced according to the sampled heightmap value along the ground plane’s normal vector. The perspective mapping of the grid results in a view-dependent, continuous level-of-detail approximation of the terrain dataset.\n\nPGM is a simple and elegant terrain rendering algorithm, however, as the camera hovers over the terrain, projected vertex positions slide over the terrain. This leads to the underlying static terrain surface changing shape slightly from frame to frame. We address these swimming artifacts by introducing four improvements: tailoring the projected grid, which pushes most otherwise culled vertices back into the view frustum, redistributing grid vertices according to an importance function for more faithful mipmap selection when sampling the heightmap, local terrain edge search for vertices within a certain proximity to the camera, and exploiting temporal coherence between frames. While our algorithm cannot guarantee a maximum screen-space error, it nevertheless reduces PGM’s inherent temporal aliasing artifacts considerably.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 480, "name": "houska-2020-IPGM-image.jpg", "type": "image/jpeg", "size": 73012, "path": "Publication:houska-2020-IPGM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 782 ], "date_end": "2020-02-07", "date_start": "2009-01-01", "diploma_examina": "2020-02-07", "matrikelnr": "9907459", "open_access": "yes", "supervisor": [ 452, 193 ], "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 480, "name": "houska-2020-IPGM-image.jpg", "type": "image/jpeg", "size": 73012, "path": "Publication:houska-2020-IPGM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "houska-2020-IPGM-poster.pdf", "type": "application/pdf", "size": 2273192, "path": "Publication:houska-2020-IPGM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "houska-2020-IPGM-thesis.pdf", "type": "application/pdf", "size": 12544262, "path": "Publication:houska-2020-IPGM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/houska-2020-IPGM-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/houska-2020-IPGM/", "__class": "Publication" }, { "id": "rumpelnik_martin_2020_PRM", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Planetary Rendering with Mesh Shaders", "date": "2020-02", "abstract": "Planetary rendering solutions often suffer from artifacts or low performance when rendering very big terrains with high details. In this thesis, we present a method that targets real-time applications and therefore aims to achieve high performance. The method can be applied with an arbitrary amount of detail, which enables stable performance under runtime or hardware restriction. In contrast to existing methods, like quadtrees and clipmaps, our method avoids artifacts, such as popping or swimming, as much as possible. The method submits coarse, rectangular regions of cells around the viewer to NVidia’s new geometry pipeline that was introduced with their Turing Architecture. Due to the capabilities of the new pipeline, we can make efficient level-of-detail decisions on the graphics processing unit (GPU) and produce work to create circular regions from the rectangular ones. These circular regions provide uniform terrain resolution for the viewer in all directions, while maintaining low rendering times.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1346, "image_height": 952, "name": "rumpelnik_martin_2020_PRM-image.png", "type": "image/png", "size": 667153, "path": "Publication:rumpelnik_martin_2020_PRM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1702 ], "date_end": "2020-02-24", "date_start": "2019-06", "matrikelnr": "01633397", "supervisor": [ 193, 1650 ], "research_areas": [ "Geometry", "Rendering" ], "keywords": [ "rendering", "real-time", "GPU", "terrain" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1346, "image_height": 952, "name": "rumpelnik_martin_2020_PRM-image.png", "type": "image/png", "size": 667153, "path": "Publication:rumpelnik_martin_2020_PRM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image:thumb{{size}}.png" }, { "description": null, "filetitle": "image2", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 978, "image_height": 985, "name": "rumpelnik_martin_2020_PRM-image2.png", "type": "image/png", "size": 990356, "path": "Publication:rumpelnik_martin_2020_PRM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image2.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-image2:thumb{{size}}.png" }, { "description": null, "filetitle": "Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "rumpelnik_martin_2020_PRM-Thesis.pdf", "type": "application/pdf", "size": 32373464, "path": "Publication:rumpelnik_martin_2020_PRM", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/rumpelnik_martin_2020_PRM-Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "3DSpatialization", "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/rumpelnik_martin_2020_PRM/", "__class": "Publication" }, { "id": "raidou_shonan167", "type_id": "misc", "tu_id": null, "repositum_id": null, "title": "NII Shonan Meeting Report No. 167: Formalizing Biological and Medical Visualization", "date": "2020-02", "abstract": "Medicine and biology are among the most important research fields, having a significant impact on humans and their health. For decades, these fields have been highly dependent on visualization—establishing a tight coupling which is crucial for the development of visualization techniques, designed exclusively for the disciplines of medicine and biology. These visualization techniques can be generalized by the term Biological and Medical Visualization—for short,BioMedical Visualization. BioMedical Visualization is not only an enabler for medical diagnosis and treatment, but also an influential component of today’s life science research. Many BioMedical domains can now be studied at various scales and dimensions, with different imaging modalities and simulations, and for a variety of purposes. Accordingly, BioMedical Visualization has also innumerable contributions in industrial applications. However, despite its proven scientific maturity and societal value, BioMedical Visualization is often treated within Computer Science as a mere application subdomain of the broader field of Visualization.To enable BioMedical Visualization to further thrive, it is important to formalize its characteristics independently from the general field of Visualization.Also, several lessons learnt within the context of BioMedical Visualization may be applicable and extensible to other application domains or to the parent field of Visualization. Formalization has become particularly urgent, with the latest advances of BioMedical Visualization—in particular, with respect to dealing with Big Data Visualization, e.g., for the visualization of multi-scale, multi-modal,cohort, or computational biology data. Rapid changes and new opportunities in the field, also regarding the incorporation of Artificial Intelligence with“human-in-the-loop” concepts within the field of Visual Analytics, compel further this formalization. By enabling the BioMedical Visualization community to have intensive discussions on the systematization of current knowledge, we can adequately prepare ourselves for future prospects and challenges, while also contributing to the broader Visualization community.\nDuring this 4-day seminar, which was the 150th NII Shonan meeting to be organized, we brought together 25 visualization experts from diverse institutions,backgrounds and expertise to discuss, identify, formalize, and document the specifics of our field. This has been a great opportunity to cover a range of relevant and contemporary topics, and as a systematic effort towards establishing better fundaments for the field and towards determining novel future challenges.In the upcoming sections of this report, we summarize the content of invited talks and of the eight main topics that were discussed within the working groups during the seminar.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1410, 1248, 818, 951, 590 ], "note": "ISSN 2186-7437", "number": "TR-193-02-2020-1", "open_access": "yes", "research_areas": [ "BioVis", "MedVis" ], "keywords": [], "weblinks": [ { "href": "https://shonan.nii.ac.jp/seminars/167/", "caption": "workshop page", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "report", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 2497, "preview_image_height": 1361, "name": "raidou_shonan167-report.pdf", "type": "application/pdf", "size": 2764706, "path": "Publication:raidou_shonan167", "preview_name": "raidou_shonan167-report:preview.PNG", "preview_type": "image/png", "preview_size": 332855, "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_shonan167/raidou_shonan167-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_shonan167/raidou_shonan167-report:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_shonan167/", "__class": "Publication" }, { "id": "PUEYO-2019-SCL", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Shrinking City Layouts", "date": "2020-02", "abstract": "One important use of realistic city environments is in the video game industry. When a company works on a game whose action occurs in a real-world environment, a team of designers usually creates a simplified model of the real city. In particular, the resulting city is desired to be smaller in extent to increase playability and fun, avoiding long walks and “boring” neighborhoods. This is manual work, usually started from scratch, where the first step is to take the original city map as input, and from it create the street network of the final city, removing insignificant streets and bringing important places closer together in the process. This first draft of the city street network is like a kind of skeleton with the most important places connected, from which the artist can (and should) start working until the desired result is obtained. In this paper, we propose a solution to automatically generate such a first simplified street network draft. This is achieved by using the well-established seam-carving technique applied to a sckeleton of the city layout, built with the important landmarks and streets of the city. The output that our process provides is a street network that reduces the city area as much as the designer wants, preserving landmarks and key streets, while keeping the relative positions between them. For this, we run a shrinking process that reduces the area in an irregular way, prioritizing the removal of areas of less importance. This way, we achieve a smaller city but retain the essence of the real-world one. To further help the designer, we also present an automatic filling algorithm that adds unimportant streets to the shrunken skeleton.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1717, 1718, 440, 193, 1719 ], "doi": "10.1016/j.cag.2019.11.004", "first_published": "2019-11-22", "issn": "0097-8493", "journal": "Computers & Graphics", "open_access": "no", "pages_from": "15", "pages_to": "26", "volume": "86", "research_areas": [ "Modeling" ], "keywords": [ "procedural modeling", "computer games" ], "weblinks": [], "files": [], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/PUEYO-2019-SCL/", "__class": "Publication" }, { "id": "Luidolt-2020-DA", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/1203", "title": "Perception of Light in Virtual Reality", "date": "2020-02", "abstract": "The perception of light and light incidence in the human eye is substantially different in real-world scenarios and virtual reality (VR) simulations. Standard low dynamic range displays, as used in common VR headsets, are not able to replicate the same light intensities we see in reality. Therefore, light phenomenons, such as temporal eye adaptation, perceptual glare, visual acuity reduction and scotopic color vision need to be simulated to generate realistic images. Even though, a physically based simulation of these effects could increase the perceived reality of VR applications, this topic has not been thoroughly researched yet. \nWe propose a post-processing workflow for VR and augmented reality (AR), using eye tracking, that is based on medical studies of the healthy human eye and is able to run in real time, to simulate light effects as close to reality as possible. We improve an existing temporal eye adaptation algorithm to be view-dependent. We adapt a medically based glare simulation to run in VR and AR. Additionally, we add eye tracking to adjust the glare intensity according to the viewing direction and the glare appearance depending on the user’s pupil size. We propose a new function fit for the reduction of visual acuity in VR head mounted displays. Finally, we include scotopic color vision for more realistic rendering of low-light scenes. \nWe conducted a primarily qualitative pilot study, comparing a real-world low-light scene to our VR simulation through individual, perceptual evaluation. Most participants mentioned, that the simulation of temporal eye adaptation, visual acuity reduction and scotopic color vision was similar or the same as their own perception in the real world. However, further work is necessary to improve the appearance and movement of our proposed glare kernel. We conclude, that our work has laid a ground base for further research regarding the simulation and individual adaptation to the perception of light in VR.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1920, "image_height": 1080, "name": "Luidolt-2020-DA-image.png", "type": "image/png", "size": 1606001, "path": "Publication:Luidolt-2020-DA", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1577 ], "date_end": "2020-02-02", "date_start": "2019-04", "diploma_examina": "2020-02-10", "matrikelnr": "01427250 ", "supervisor": [ 1030, 193 ], "research_areas": [ "Perception", "Rendering", "VR" ], "keywords": [ "perception", "temporal eye adaptation", "glare", "virtual reality", "scotopic vision", "visual acuity reduction", "augmented reality" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1920, "image_height": 1080, "name": "Luidolt-2020-DA-image.png", "type": "image/png", "size": 1606001, "path": "Publication:Luidolt-2020-DA", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Luidolt-2020-DA-poster.pdf", "type": "application/pdf", "size": 6507701, "path": "Publication:Luidolt-2020-DA", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Luidolt-2020-DA-thesis.pdf", "type": "application/pdf", "size": 15289421, "path": "Publication:Luidolt-2020-DA", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/Luidolt-2020-DA-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Luidolt-2020-DA/", "__class": "Publication" }, { "id": "Groeller_V1_2020", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/87163", "title": "Interactive Visual Analysis in the Computational Sciences", "date": "2020-01-29", "abstract": "Visualization and visual computing use computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analyses, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. The simultaneous exploration and visualization of spatial and abstract information is an important case in point. Several examples from the computational sciences will be discussed in detail. These concern: parameter studies of dataset series; visual analytics for the exploration and assessment of segmentation errors; quantitative visual analytics with structured brushing and linked statistics; visual comparison of 3D volumes through space-filling curves. Given the amplified data variability, interactive visual data analyses are likely to gain in importance in the future. Research challenges and directions are sketched at the end of the talk.\n", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 166 ], "event": "High Visual Computing (HiVisComp) 2020", "location": "Hotel Praha, Ore Mountains, Czech Republic", "open_access": "yes", "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Groeller_V1_2020/", "__class": "Publication" }, { "id": "Cornel_2020", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/1225", "title": "Interactive Visualization of Simulation Data for GeospatialDecision Support", "date": "2020-01-19", "abstract": "Floods are catastrophic events that claim thousands of human lives every year. For theprediction of these events, interactive decision support systems with integrated floodsimulation have become a vital tool. Recent technological advances made it possibleto simulate flooding scenarios of unprecedented scale and resolution, resulting in verylarge time-dependent data. The amount of simulation data is further amplified by theuse of ensemble simulations to make predictions more robust, yielding high-dimensionaland uncertain data far too large for manual exploration. New strategies are thereforeneeded to filter these data and to display only the most important information to supportdomain experts in their daily work. This includes the communication of results to decisionmakers, emergency services, stakeholders, and the general public. A modern decisionsupport system has to be able to provide visual results that are useful for domain experts,but also comprehensible for larger audiences. Furthermore, for an efficient workflow, theentire process of simulation, analysis, and visualization has to happen in an interactivefashion, putting serious time constraints on the system.In this thesis, we present novel visualization techniques for time-dependent and uncertainflood, logistics, and pedestrian simulation data for an interactive decision support system.As the heterogeneous tasks in flood management require very diverse visualizations fordifferent target audiences, we provide solutions to key tasks in the form of task-specificand user-specific visualizations. This allows the user to show or hide detailed informationon demand to obtain comprehensible and aesthetic visualizations to support the task athand. In order to identify the impact of flooding incidents on a building of interest, onlya small subset of all available data is relevant, which is why we propose a solution toisolate this information from the massive simulation data. To communicate the inherentuncertainty of resulting predictions of damages and hazards, we introduce a consistentstyle for visualizing the uncertainty within the geospatial context. Instead of directlyshowing simulation data in a time-dependent manner, we propose the use of bidirectionalflow maps with multiple components as a simplified representation of arbitrary materialflows. For the communication of flood risks in a comprehensible way, however, thedirect visualization of simulation data over time can be desired. Apart from the obviouschallenges of the complex simulation data, the discrete nature of the data introducesadditional problems for the realistic visualization of water surfaces, for which we proposerobust solutions suitable for real-time applications. All of our findings have been acquiredthrough a continuous collaboration with domain experts from several flood-related fieldsof work. The thorough evaluation of our work by these experts confirms the relevanceand usefulness of our presented solutions. \n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 436, "image_height": 277, "name": "Cornel_2020-image.JPG", "type": "image/jpeg", "size": 53075, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 877 ], "doi": "10.34726/hss.2020.75784", "duration": "5", "matrikelnr": "0726194", "open_access": "yes", "pages": "167", "reviewer_1": [ 1745 ], "reviewer_2": [ 823 ], "rigorosum": "2020-01", "supervisor": [ 166 ], "research_areas": [ "InfoVis" ], "keywords": [ "Interactive visualization", "uncertainty", "flood management", "decision support", "flood simulation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 436, "image_height": 277, "name": "Cornel_2020-image.JPG", "type": "image/jpeg", "size": 53075, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-image:thumb{{size}}.png" }, { "description": null, "filetitle": "PhD Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Cornel_2020-PhD Thesis.pdf", "type": "application/pdf", "size": 43001362, "path": "Publication:Cornel_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-PhD Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/Cornel_2020-PhD Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Cornel_2020/", "__class": "Publication" }, { "id": "raidou_2020Onc", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141410", "title": "Principles of Visualization in Radiation Oncology", "date": "2020-01-15", "abstract": "Background: Medical visualization employs elements from computer graphics to create meaningful, interactive visual representations of medical data, and it has become an influential field of research for many advanced applications like radiation oncology, among others. Visual representations employ the user’s cognitive capabilities to support and accelerate diagnostic, planning, and quality assurance workflows based on involved patient data. Summary: This article discusses the basic underlying principles of visualization in the application domain of radiation oncology. The main visualization strategies, such as slice-based representations and surface and volume rendering are presented. Interaction topics, i.e., the combination of visualization and automated analysis methods, are also discussed. Key Messages: Slice-based representations are a common approach in radiation oncology, while volume visualization also has a long-standing history in the field. Perception within both representations can benefit further from advanced approaches, such as image fusion and multivolume or hybrid rendering. While traditional slice-based and volume representations keep evolving, the dimensionality and complexity of medical data are also increasing. To address this, visual analytics strategies are valuable, particularly for cohort or uncertainty visualization. Interactive visual analytics approaches represent a new opportunity to integrate knowledgeable experts and their cognitive abilities in exploratory processes which cannot be conducted by solely automatized methods.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1651, 563, 231, 1410 ], "doi": "https://doi.org/10.1159/000504940", "journal": "Oncology and Informatics", "open_access": "yes", "pages_from": "1", "pages_to": "11", "volume": "1", "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "raidou_2020Onc-paper.pdf", "type": "application/pdf", "size": 900790, "path": "Publication:raidou_2020Onc", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_2020Onc/raidou_2020Onc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_2020Onc/raidou_2020Onc-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_2020Onc/", "__class": "Publication" }, { "id": "TOMASCHITZ-2020-EP", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/1251", "title": "Erlernen von Programmieren an Oberstufen der Gymnasien Österreichs durch Computergrafik-unterstützte Ausgabe", "date": "2020-01", "abstract": "Learning programming is a challenging task as several skills, have to be learned. Some of those are mathematical knowledge, logical knowledge and knowledge about handling the computer. By having these skills, someone could start learning programming in a more or less effective way. However, the skill „programming“ describes the way of thinking some-one should achieve, not only writing correct code with the help of a programming language.\n\nBut learning to think like a programmer needs time, as described above. Many different skills for solving software problems are needed. Therefore the way of learning is essential. Many books teaching how to program only show the right way of using a programming language and do not focus on the essential part: the way of thinking. Another problem shown in past researches is based on the way of teaching. Motivated by the right factors, student could achieve better results when learning new content. Using the method of active learning with combined audio and video sources for teaching caused much more effective learning results as humans are trained to remember faster and longer what they have seen or heard.\n\nIn Austria, students are forced to learn a variety of clearly separated topics within three years to gain knowledge about informatics before leaving high school. Breaking it down, the time for learning programming basics within a year are about 8 weeks, having 2 units à 50 minutes. So time is short and the teacher is forced to use an effective way to teach programming and show students how to think like a programmer.\n\nHaving all these facts in mind, a method shown in this document is developed that is effective enough to achieve the goal of an effective learning curve. As personally experienced, learning programming is much easier having the right way of representing what is going on. The „classic“ way of showing what is going on is by having textual output, while the method developed here uses graphical output to represent what has been programmed. The aim of this research is to analyse the effectiveness of graphical output over textual out-put. The structure of the document is as follows: analysis of actual research, basics used in the learning method developed and comparison between programming with textual output and programming with graphical output. In the end, the results are shown and a perspec-tive is shown.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1105, "image_height": 640, "name": "TOMASCHITZ-2020-EP-image.jpg", "type": "image/jpeg", "size": 28990, "path": "Publication:TOMASCHITZ-2020-EP", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1759 ], "date_end": "2020-03", "date_start": "2018-10", "diploma_examina": "2020-03-02", "doi": "10.34726/hss.2020.62900", "matrikelnr": "00051491", "open_access": "yes", "pages": "112", "supervisor": [ 193 ], "research_areas": [], "keywords": [ "Lernmethode", "Lerneffizienz", "Programmieren", "textuell", "visuell" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1105, "image_height": 640, "name": "TOMASCHITZ-2020-EP-image.jpg", "type": "image/jpeg", "size": 28990, "path": "Publication:TOMASCHITZ-2020-EP", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "TOMASCHITZ-2020-EP-poster.pdf", "type": "application/pdf", "size": 514733, "path": "Publication:TOMASCHITZ-2020-EP", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-poster:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "TOMASCHITZ-2020-EP-thesis.pdf", "type": "application/pdf", "size": 5691212, "path": "Publication:TOMASCHITZ-2020-EP", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/TOMASCHITZ-2020-EP-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/TOMASCHITZ-2020-EP/", "__class": "Publication" }, { "id": "Halladjian_2020", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/141411", "title": "ScaleTrotter: Illustrative Visual Travels Across Negative Scales", "date": "2020-01", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "scale_trotter", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 770, "image_height": 838, "name": "Halladjian_2020-scale_trotter.png", "type": "image/png", "size": 746352, "path": "Publication:Halladjian_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-scale_trotter.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-scale_trotter:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1665, 1263, 1383, 166, 171, 960 ], "date_from": "2019-10", "date_to": "2019-10", "event": "IEEE Vis 2019", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1665 ], "number": "1", "volume": "26", "research_areas": [ "BioVis", "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Halladjian_2020-paper.pdf", "type": "application/pdf", "size": 14976666, "path": "Publication:Halladjian_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "scale_trotter", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 770, "image_height": 838, "name": "Halladjian_2020-scale_trotter.png", "type": "image/png", "size": 746352, "path": "Publication:Halladjian_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-scale_trotter.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-scale_trotter:thumb{{size}}.png" } ], "projects_workgroups": [ "Illustrare" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/", "__class": "Publication" }, { "id": "heim-gall-2020-dde", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "DDE - Dynamic Data Explorer: Dynamic data exploration in a collaborative spatial-aware environment", "date": "2020-01", "abstract": "Collaborative decision-making has become an integral part of the analysis process aiming to get insight into multivariate\ndata. To further encourage this workflow numerous co-located, multi-user systems have been developed consisting of large\nmulti-touch screens or interactive tabletops. But such frameworks are typically expensive and unavailable outside dedicated\nenvironments as for example laboratories. Therefore we developed the Dynamic Data Explorer, short DDE, a multi-user system\nthat enables users to join, in an ad-hoc manner, with their own mobile devices. Since forming groups should be possible in\nvarious locations, the tracking system, enabling spatial awareness of the devices, has to be light-weight and small. Near Field\nCommunication (NFC) is a widespread transmission technology which fulfils these properties and is used in our framework to\nenable different side-by-side arrangements of devices. This allows users to explore multivarate data visualizations on a system\nwhere the number of devices and their set-up can be modified at all times.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "setup", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2220, "image_height": 1900, "name": "heim-gall-2020-dde-setup.jpg", "type": "image/jpeg", "size": 1379498, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1354, 1355 ], "date_end": "2020-01", "date_start": "2019-04", "matrikelnr": "1226809, 1225540", "supervisor": [ 1110, 1643 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://github.com/nonsens949/Practicum/wiki", "caption": "GitHub", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "heim-gall-2020-dde-report.pdf", "type": "application/pdf", "size": 1583282, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-report:thumb{{size}}.png" }, { "description": null, "filetitle": "setup", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2220, "image_height": 1900, "name": "heim-gall-2020-dde-setup.jpg", "type": "image/jpeg", "size": 1379498, "path": "Publication:heim-gall-2020-dde", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/heim-gall-2020-dde-setup:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/heim-gall-2020-dde/", "__class": "Publication" }, { "id": "nguyen_2020-covid", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models", "date": "2020", "abstract": "We present a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models. Resulting 3D models are based on few 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. Our new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we learn statistical properties of various structural aspects, such as the outer membrane shape, spatial properties and distribution characteristics of the macromolecular elements on the membrane. This information is utilized in 3D model construction. Once all imaging evidence is incorporated in the model, additional information can be incorporated by interactively defining rules that spatially characterize the rest of the biological entity, such as mutual interactions among macromolecules, their distances and orientations to other structures. These rules are defined through an intuitive 3D interactive visualization and modeling feedback loop. We demonstrate the utility of our approach on a use case of the modeling procedure of the SARS-CoV-2 virus particle ultrastructure. Its first complete atomistic model, which we present here, can steer biological research to new promising directions in fighting spread of the virus.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2160, "image_height": 1824, "name": "nguyen_2020-covid-image.png", "type": "image/png", "size": 3574056, "path": "Publication:nguyen_2020-covid", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1788, 1789, 1285, 1791, 194, 1792, 935, 1260, 1365, 171 ], "date_from": "2020", "date_to": "2020 (to appear)", "event": "IEEE VIS 2020", "journal": "IEEE Transactions on Visualization and Computer Graphics", "research_areas": [ "BioVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2160, "image_height": 1824, "name": "nguyen_2020-covid-image.png", "type": "image/png", "size": 3574056, "path": "Publication:nguyen_2020-covid", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/", "__class": "Publication" }, { "id": "amirkhanov2020visual", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visual Analytics in Dental Aesthetics", "date": "2020", "abstract": "Dental healthcare increasingly employs computer-aided design software,\nto provide patients with high-quality dental prosthetic devices. In\nmodern dental reconstruction, dental technicians address the unique\nanatomy of each patient individually, by capturing the dental impression\nand measuring the mandibular movements. Subsequently, dental technicians\ndesign a custom denture that fits the patient from a functional point of\nview. The current workflow does not include a systematic analysis of\naesthetics, and dental technicians rely only on an aesthetically\npleasing mock-up that they discuss with the patient, and on their\nexperience. Therefore, the final denture aesthetics remain unknown until\nthe dental technicians incorporate the denture into the patient. In this\nwork, we present a solution that integrates aesthetics analysis into the\nfunctional workflow of dental technicians. Our solution uses a video\nrecording of the patient, to preview the denture design at any stage of\nthe denture design process. We present a teeth pose estimation technique\nthat enables denture preview and a set of linked visualizations that\nsupport dental technicians in the aesthetic design of dentures. These\nvisualizations assist dental technicians in choosing the most\naesthetically fitting preset from a library of dentures, in identifying\nthe suitable denture size, and in adjusting the denture position. We\ndemonstrate the utility of our system with four use cases, explored by a\ndental technician. Also, we performed a quantitative evaluation for\nteeth pose estimation, and an informal usability evaluation, with\npositive outcomes concerning the integration of aesthetics analysis into\nthe functional workflow.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1170, 660, 925, 1628, 1629, 166, 869 ], "doi": "https://doi.org/10.1111/cgf.14174", "journal": "Computer Graphics Forum", "number": "7", "pages": "635–646", "pages_from": "635", "pages_to": "646", "volume": "39", "research_areas": [], "keywords": [ "Applied computing -> Life and medical sciences", "Human-centered computing -> Visualization application domains" ], "weblinks": [ { "href": "https://amirkhanov.net/visual-analytics-in-dental-aesthetics/", "caption": "Official page", "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/amirkhanov2020visual/", "__class": "Publication" } ]