[ { "id": "pr10", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Curved Reflections in Large Point Clouds", "date": "2010-05", "abstract": "In the field of real-time rendering, computer graphics observes a continuously growing power of visualizing of scenes of continuously growing complexity. In the past few years, a number of rendering techniques have been developed that let the quality of the rendered images converge towards photorealism. Especially in the field of realistic scene illumination, Global Illumination (GI) techniques represent an important field of research. Previous to this work, for the first time we have applied a GI algorithm also to point clouds, which enables us to achieve realistic illumination of diffuse and glossy objects in real-time. This thesis elevates the power of visualization of this GI-Renderer to the next level. For the first time, it implements a realistic, physically based rendering of mirroring surfaces also for point clouds. Current real-time approaches addressing curved mirroring surfaces in polygon scenes either are extremely imprecise or cannot handle each arbitrary type of surface. Especially concave surfaces represent a significant difficulty for current physically based methods. Up to now, physically correct mirror reflections on complex surfaces can only be produced by offline algorithms.\r\nWe introduce a novel rendering technique called \"Screen-space curved reflections\", which enables us to produce physically correct mirror reflections on arbitrarily complex surfaces. Our method bases on the approach, for each point in the scene to find the pixel in the framebuffer that contains its reflecting surface point. This is achieved by the application of a fast 2D root finding in a new error function called \"mirror-space error function\". Although our method raises high demands on the hardware, we are able to render common scenes at interactive frame rates.", "authors_et_al": false, "substitute": null, "main_image": { "description": "mirroring Stanford Bunny point cloud rendered with SSCR", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 399, "image_height": 360, "name": "pr10-image.png", "type": "image/png", "size": 257065, "path": "Publication:pr10", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 799, "drupal_id": 221, "orcid_id": "0000-0002-5167-1977", "website": "https://www.cg.tuwien.ac.at/staff/ReinholdPreiner", "firstname": "Reinhold", "lastname": "Preiner", "searchname": 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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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"https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "journal": "Computer Graphics & Geometry", "number": "1", "pages_from": "2", "pages_to": "16", "volume": "12", "research_areas": [ { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. 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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "start_date": "2006-10-01", "end_date": "2009-12-31", "leader_id": 193, "logo": null, "funding_organisations": [ { "id": "FFF", "contract_number": "812126", "comment": null } ], "research_areas": [ "Rendering" ], "publications": [ "BARSUKOV-2010-NEPC", "Bogner-2008-MTh", "PLUCH-2009-ANP", "pr10", "preiner_2010_GIPC", "PREINER-2009-GIPC", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "WIMMER-2006-DWN", "WIMMER-2006-IP" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Scanopy", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/", "__class": "Publication" }, { "id": "SCHEIBLAUER-2009-IDCE", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Interactive Domitilla Catacomb Exploration", "date": "2009-09", "abstract": "In this paper we present an approach for interactive visualization and manipulation of huge point clouds. Archaeological monuments like the Domitilla Catacomb in Rome lead to data sets surpassing 1 Billion points or 20GB of storage space, which makes standard techniques like mesh conversion or in-core point-based rendering infeasible. Our system uses an out-of-core octree structure and a number of interactive editing tools to enable many archaeological tasks to be carried out on the whole point cloud that would not be possible using traditional methods. We allow fast selection, insertion and deletion of points, and through out-of-core rendering, the frame rate always stays above 20 frames per second on a fast workstation. \nTo the best of our knowledge, this is the first interactive visualization of the complete data set of a large subterranean catacomb, and we show that direct point cloud visualization on the complete data set of a scan campaign is an important tool in archaeological practice.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1600, "image_height": 1076, "name": "SCHEIBLAUER-2009-IDCE-image.jpg", "type": "image/jpeg", "size": 269202, "path": "Publication:SCHEIBLAUER-2009-IDCE", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/SCHEIBLAUER-2009-IDCE/SCHEIBLAUER-2009-IDCE-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": 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"Tragust-2014-master-thesis", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=614", "__class": "Author" } ], "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ { "id": "Scanopy", "workgroup_id": "rend", "drupal_id": 4246, "drupal_path": "/research/projects/Scanopy", "name": "SCANOPY - Scan Data Organisation, Processing and Display", "name_de": null, "short_title": "Scanopy", "website": null, "status": "active", "short_abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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Point clouds resulting from these laser scans can consist of hundreds of millions of points. To get a clean model from this vast amount of data needs several person months. Instead we try to visualize the data directly, so archeologists can have a quick overview of the already scanned areas (e.g., during a scanning campaign). The models in our viewer are combined point clouds from several scan positions, and it is possible to add new point clouds to an existing model. We also allow for deleting points from the model. Furthermore we developed a heuristic to estimate point sizes, which enables the viewer to display surfaces as closed objects without a special preprocessing step. 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"supervisor", "ordernum": 0 }, { "publ_id": "PREINER-2009-GIPC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Scheiblauer-2008-DCW", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHEIBLAUER-2009-IDCE", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "scheiblauer-2011-chnt", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "scheiblauer-2012-chnt", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "scheiblauer-2013-wscg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Tragust-2012-GMHPC", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Tragust-2014-master-thesis", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=614", "__class": "Author" } ], "booktitle": "Proceedings of the 13th International Congress on Cultural Heritage and New Technologies", "date_from": "2008-11-03", "date_to": "2008-11-05", "isbn": "978-3-85161-016-1", "lecturer": [ { "id": 614, 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. 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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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The\nnovelty here is that we do not make any assumptions about sampling\ndensity or availability of normal vectors for the points. This is\nvery important because such information is available only after\nlengthy postprocessing of scanned datasets, whereas users want to\ninteract with the dataset immediately. Instant Points is an\nout-of-core algorithm that makes use of nested octrees and an\nenhanced version of sequential point trees.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Altar", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 640, "name": "WIMMER-2006-IP-Altar.png", "type": "image/png", "size": 630140, "path": "Publication:WIMMER-2006-IP", "url": "https://www.cg.tuwien.ac.at/research/publications/2006/WIMMER-2006-IP/WIMMER-2006-IP-Altar.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2006/WIMMER-2006-IP/WIMMER-2006-IP-Altar:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", 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The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

\r\n", "abstract": "

The aim of the Scanopy project is to provide efficient algorithms for working with 3D laser scan data. The first main challenge is to improve the quality of raw scan data via filtering, scan completion and repair, making use of image information and symmetries. The second challenge is to and second to develop efficient data structures and algorithm to allow displaying huge point-based models. The third challenge is to improve the appearance of the models via lighting and relighting.

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