[ { "id": "Preiner_2019", "type_id": "journalpaper", "tu_id": 282850, "repositum_id": null, "title": "Gaussian-Product Subdivision Surfaces", "date": "2019-07", "abstract": "Probabilistic distribution models like Gaussian mixtures have shown great\npotential for improving both the quality and speed of several geometric operators. This is largely due to their ability to model large fuzzy data using only a reduced set of atomic distributions, allowing for large compression rates at minimal information loss. We introduce a new surface model that utilizes these qualities of Gaussian mixtures for the definition and control of a parametric smooth surface. Our approach is based on an enriched mesh data structure, which describes the probability distribution of spatial surface locations around each vertex via a Gaussian covariance matrix. By incorporating this additional covariance information, we show how to define a smooth surface via a nonlinear probabilistic subdivision operator based on products of Gaussians, which is able to capture rich details at fixed control mesh resolution. This entails new applications in surface reconstruction,\nmodeling, and geometric compression.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 802, "image_height": 537, "name": "Preiner_2019-image.jpg", "type": "image/jpeg", "size": 184075, "path": "Publication:Preiner_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799, 1518, 193 ], "date_from": "2019-07-28", "date_to": "2019-08-01", "doi": "10.1145/3306346.3323026", "event": "ACM SIGGRAPH 2019", "issn": "0730-0301", "journal": "ACM Transactions on Graphics", "lecturer": [ 799 ], "location": "Los Angeles, USA", "number": "4", "open_access": "yes", "pages_from": "35:1", "pages_to": "35:11", "volume": "38", "research_areas": [ "Geometry" ], "keywords": [ "Gaussian mixtures", "surface reconstruction", "subdivision surfaces" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 802, "image_height": 537, "name": "Preiner_2019-image.jpg", "type": "image/jpeg", "size": 184075, "path": "Publication:Preiner_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Preiner_2019-Paper.pdf", "type": "application/pdf", "size": 22292400, "path": "Publication:Preiner_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/Preiner_2019-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Preiner_2019/", "__class": "Publication" }, { "id": "preiner_2017_phd", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Dynamic and Probabilistic Point-Cloud Processing", "date": "2017-10", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1030, "image_height": 556, "name": "preiner_2017_phd-teaser.png", "type": "image/png", "size": 554220, "path": "Publication:preiner_2017_phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799 ], "date_end": "2017", "date_start": "2010", "matrikelnr": "0430380", "reviewer_1": [ 1510 ], "reviewer_2": [ 1511 ], "rigorosum": "2017-10-13", "supervisor": [ 193 ], "research_areas": [ "Geometry", "Modeling", "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1030, "image_height": 556, "name": "preiner_2017_phd-teaser.png", "type": "image/png", "size": 554220, "path": "Publication:preiner_2017_phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "preiner_2017_phd-thesis.pdf", "type": "application/pdf", "size": 223842034, "path": "Publication:preiner_2017_phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/preiner_2017_phd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/preiner_2017_phd/", "__class": "Publication" }, { "id": "TR1862162", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Volume Ensembles Based on Local Features", "date": "2016-05", "abstract": "Ensemble datasets describe a specific phenomenon (e.g., a simulation scenario or a measurements series) through a large set of individual ensemble members. These individual members typically do not differ too much from each other but rather feature slightly changing characteristics. In many cases, the ensemble members are defined in 3D space, which implies severe challenges when exploring the complete ensembles such as handling occlusions, focus and context or its sheer datasize. In this paper we address these challenges and put our focus on the exploration of local features in 3D volumetric ensemble datasets, not only by visualizing local characteristics, but also by identifying connections to other local features with similar characteristics in the data. We evaluate the variance in the dataset and use the the spatial median (medoid) of the ensemble to visualize the differences in the dataset. This medoid is subsequently used as a representative of the ensemble in 3D. The variance information is used to guide users during the exploration, as regions of high variance also indicate larger changes within the ensemble members. The local characteristics of the regions can be explored by using our proposed 3D probing widgets. These widgets consist of a 3D sphere, which can be positioned at any point in 3D space. While moving a widget, the local data characteristics at the corresponding position are shown in a separate detail view, which depicts the local outliers and their surfaces in comparison to the medoid surface. The 3D probing widgets can also be fixed at a user-defined position of interest. The fixed probing widgets are arranged in a similarity graph to indicate similar local data characteristics. The similarity graph thus allows to explore whether high variances in a certain region are caused by the same dataset members or not. Finally, it is also possible to compare a single member against the rest of the ensemble. We evaluate our technique through two demonstration cases using volumetric multi-label segmentation mask datasets, two from the\nindustrial domain and two from the medical domain.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 599, "image_height": 277, "name": "TR1862162-teaser.png", "type": "image/png", "size": 498904, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950, 1191, 799, 983, 166, 161, 611 ], "number": "TR-186-2-16-2", "research_areas": [ "InfoVis" ], "keywords": [ "ensemble visualization", "guided local exploration", "variance analysis" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 599, "image_height": 277, "name": "TR1862162-teaser.png", "type": "image/png", "size": 498904, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "tech-report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "TR1862162-tech-report.pdf", "type": "application/pdf", "size": 5108648, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-tech-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-tech-report:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/", "__class": "Publication" }, { "id": "arikan-2015-dmrt", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Multi-Depth-Map Raytracing for Efficient Large-Scene Reconstruction", "date": "2016-02", "abstract": "With the enormous advances of the acquisition technology over the last years, fast processing and high-quality\nvisualization of large point clouds have gained increasing attention. Commonly, a mesh surface is reconstructed from the point\ncloud and a high-resolution texture is generated over the mesh from the images taken at the site to represent surface materials. However, this global reconstruction and texturing approach becomes impractical with increasing data sizes. Recently, due to its\npotential for scalability and extensibility, a method for texturing a set of depth maps in a preprocessing and stitching them at runtime has been proposed to represent large scenes. However, the rendering performance of this method is strongly dependent on the number of depth maps and their resolution. Moreover, for the proposed scene representation, every single depth map has to be textured by the images, which in practice heavily increases processing costs. In this paper, we present a novel method\nto break these dependencies by introducing an efficient raytracing of multiple depth maps. In a preprocessing phase, we first generate high-resolution textured depth maps by rendering the input points from image cameras and then perform a graph-cut\nbased optimization to assign a small subset of these points to the images. At runtime, we use the resulting point-to-image assignments (1) to identify for each view ray which depth map contains the closest ray-surface intersection and (2) to efficiently\ncompute this intersection point. The resulting algorithm accelerates both the texturing and the rendering of the depth maps by an order of magnitude.", "authors_et_al": false, "substitute": null, "main_image": { "description": "teaser image", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 2855, "image_height": 1392, "name": "arikan-2015-dmrt-image.jpg", "type": "image/jpeg", "size": 2864240, "path": "Publication:arikan-2015-dmrt", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 865, 799, 193 ], "doi": "10.1109/TVCG.2015.2430333", "issn": "1077-2626", "journal": "IEEE Transactions on Visualization & Computer Graphics", "number": "2", "pages_from": "1127", "pages_to": "1137", "volume": "22", "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [ { "href": "http://http://dx.doi.org/10.1109/TVCG.2015.2430333", "caption": "doi", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "draft", "main_file": true, "use_in_gallery": false, "access": "public", "name": "arikan-2015-dmrt-draft.pdf", "type": "application/pdf", "size": 1697346, "path": "Publication:arikan-2015-dmrt", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-draft:thumb{{size}}.png" }, { "description": "teaser image", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 2855, "image_height": 1392, "name": "arikan-2015-dmrt-image.jpg", "type": "image/jpeg", "size": 2864240, "path": "Publication:arikan-2015-dmrt", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-image:thumb{{size}}.png" }, { "description": "[45MB]", "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "arikan-2015-dmrt-video.mp4", "type": "video/mp4", "size": 47571465, "path": "Publication:arikan-2015-dmrt", "preview_name": "arikan-2015-dmrt-video:preview.png", "preview_type": "image/jpeg", "preview_size": 91344, "url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/arikan-2015-dmrt-video:video.mp4" } ], "projects_workgroups": [ "Harvest4D" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/arikan-2015-dmrt/", "__class": "Publication" }, { "id": "ymca", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "YMCA - Your Mesh Comparison Application", "date": "2014-11", "abstract": "Polygonal meshes can be created in several different ways. In this paper we focus on the reconstruction of meshes from point clouds, which are sets of points in 3D. Several algorithms that tackle this task already exist, but they have different benefits and drawbacks, which leads to a large number of possible reconstruction results (i.e., meshes). The evaluation of those techniques requires extensive comparisons between different meshes which is up to now done by either placing images of rendered meshes side-by-side, or by encoding differences by heat maps. A major drawback of both approaches is that they do not scale well with the number of meshes. This paper introduces a new comparative visual analysis technique for 3D meshes which enables the simultaneous comparison of several meshes and allows for the interactive exploration of their differences. Our approach gives an overview of the differences of the input meshes in a 2D view. By selecting certain areas of interest, the user can switch to a 3D representation and explore the spatial differences in detail. To inspect local variations, we provide a magic lens tool in 3D. The location and size of the lens provide further information on the variations of the reconstructions in the selected area. With our comparative visualization approach, differences between several mesh reconstruction algorithms can be easily localized and inspected.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 644, "image_height": 661, "name": "ymca-teaser.png", "type": "image/png", "size": 1279857, "path": "Publication:ymca", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 950, 799, 808, 193, 166, 161 ], "booktitle": "IEEE Visual Analytics Science and Technology", "date_from": "2014-11-09", "date_to": "2014-11-14", "lecturer": [ 950 ], "location": "Paris, France", "note": "http://dx.doi.org/10.1109/VAST.2014.7042491", "publisher": "IEEE Computer Society", "series": "VAST ", "research_areas": [ "InfoVis" ], "keywords": [ "mesh comparison", "3D data exploration", "focus+context", "comparative visualization", "Visual analysis" ], "weblinks": [], "files": [ { "description": "paper (authors personal copy, accepted for publication by IEEE)", "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 669, "preview_image_height": 430, "name": "ymca-paper.pdf", "type": "application/pdf", "size": 2169351, "path": "Publication:ymca", "preview_name": "ymca-paper:preview.png", "preview_type": "image/png", "preview_size": 864893, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 644, "image_height": 661, "name": "ymca-teaser.png", "type": "image/png", "size": 1279857, "path": "Publication:ymca", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-teaser:thumb{{size}}.png" }, { "description": "demonstration of the application - 4:30 min - 20.2 MB", "filetitle": "video-demo", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 64, "preview_image_height": 41, "name": "ymca-video-demo.wmv", "type": "application/octet-stream", "size": 21207342, "path": "Publication:ymca", "preview_name": "ymca-video-demo:preview.png", "preview_type": "image/png", "preview_size": 8002, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-video-demo.wmv", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/ymca-video-demo:thumb{{size}}.png" } ], "projects_workgroups": [ "ViMaL" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/ymca/", "__class": "Publication" }, { "id": "arikan-2014-pcvis", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Large-Scale Point-Cloud Visualization through Localized Textured Surface Reconstruction", "date": "2014-09", "abstract": "In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality\nrepresentation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and\nhandles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since\nour preprocessing phase requires only a minor fraction of the whole dataset at once, we provide maximum flexibility when dealing with growing datasets.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 5356, "image_height": 4850, "name": "arikan-2014-pcvis-image.jpg", "type": "image/jpeg", "size": 6686806, "path": "Publication:arikan-2014-pcvis", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 865, 799, 614, 356, 193 ], "issn": "1077-2626", "journal": "IEEE Transactions on Visualization & Computer Graphics", "number": "9", "pages_from": "1280", "pages_to": "1292", "volume": "20", "research_areas": [ "Rendering" ], "keywords": [ "image-based rendering", "large-scale models", "color", "surface representation" ], "weblinks": [ { "href": "http://doi.ieeecomputersociety.org/10.1109/TVCG.2014.2312011", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": "Acknowledgments datasets", "filetitle": "ackn", "main_file": false, "use_in_gallery": false, "access": "public", "name": "arikan-2014-pcvis-ackn.rtf", "type": "text/rtf", "size": 597, "path": "Publication:arikan-2014-pcvis", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-ackn.rtf", "thumb_image_sizes": [] }, { "description": "[13 MB]", "filetitle": "draft", "main_file": true, "use_in_gallery": false, "access": "public", "name": "arikan-2014-pcvis-draft.pdf", "type": "application/pdf", "size": 13594589, "path": "Publication:arikan-2014-pcvis", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-draft:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 5356, "image_height": 4850, "name": "arikan-2014-pcvis-image.jpg", "type": "image/jpeg", "size": 6686806, "path": "Publication:arikan-2014-pcvis", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-image:thumb{{size}}.png" }, { "description": "[33 MB]", "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "arikan-2014-pcvis-video.avi", "type": "video/x-msvideo", "size": 33911454, "path": "Publication:arikan-2014-pcvis", "preview_name": "arikan-2014-pcvis-video:preview.png", "preview_type": "image/jpeg", "preview_size": 34237, "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-video.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/arikan-2014-pcvis-video:video.mp4" } ], "projects_workgroups": [ "Harvest4D" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/arikan-2014-pcvis/", "__class": "Publication" }, { "id": "preiner2014clop", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Continuous Projection for Fast L1 Reconstruction", "date": "2014-08", "abstract": "With better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no L1-based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. 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In contrast to traditional graphics hardware methods, which rely on massive oversampling to combat aliasing issues in the rasterization process, we evaluate a closed-form solution of the associated prefilter convolution. This enables the use of a wide range of filter functions with arbitrary kernel sizes, as well as general shading methods such as texture mapping or complex illumination models. Due to the use of analytic solutions, our results are exact in the mathematical sense and provide objective ground-truth for other anti-aliasing methods and enable the rigorous comparison of different models and filters. 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Recently, the acquisition of dynamic scenes at interactive frame rates has become feasible. A high-quality visualization of the resulting point cloud stream would require a per-frame reconstruction of object surfaces. Unfortunately, reconstruction computations are still too time-consuming to be applied interactively. In this paper we present a local surface reconstruction and visualization technique that provides interactive feedback for reasonably sized point clouds, while achieving high image quality. Our method is performed entirely on the GPU and in screen pace, exploiting the efficiency of the common rasterization pipeline. The approach is very general, as no assumption is made about point connectivity or sampling density. This naturally allows combining the outputs of multiple scanners in a single visualization, which is useful for many virtual and augmented reality applications.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 982, "image_height": 832, "name": "preiner_2012_AS-image.png", "type": "image/png", "size": 1318166, "path": "Publication:preiner_2012_AS", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799, 356, 193 ], "booktitle": "Proceedings of Eurographics Symposium on Parallel Graphics and Visualization", "date_from": "2012-05-13", "date_to": "2012-05-14", "editor": "H. Childs and T. Kuhlen", "isbn": " 978-3-905674-35-4", "lecturer": [ 799 ], "location": "Cagliari", "organization": "Eurographics Association 2012", "pages_from": "139", "pages_to": "148", "research_areas": [ "Geometry" ], "keywords": [ "point clouds", "surface reconstruction", "point rendering", "Auto Splats", "KNN search", "GPU rendering", "point based rendering" ], "weblinks": [], "files": { "0": { "description": null, "filetitle": "draft", "main_file": true, "use_in_gallery": false, "access": "public", "name": "preiner_2012_AS-draft.pdf", "type": "application/pdf", "size": 14963547, "path": "Publication:preiner_2012_AS", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-draft.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-draft:thumb{{size}}.png" }, "1": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 982, "image_height": 832, "name": "preiner_2012_AS-image.png", "type": "image/png", "size": 1318166, "path": "Publication:preiner_2012_AS", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-image:thumb{{size}}.png" }, "3": { "description": null, "filetitle": "video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 640, "preview_image_height": 480, "name": "preiner_2012_AS-video.wmv", "type": "text/plain", "size": 48670503, "path": "Publication:preiner_2012_AS", "preview_name": "preiner_2012_AS-video:preview.png", "preview_type": "image/jpeg", "preview_size": 5344, "url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-video.wmv", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/preiner_2012_AS-video:thumb{{size}}.png" } }, "projects_workgroups": [ "TERAPOINTS", "Desiree" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/", "__class": "Publication" }, { "id": "TR-186-2-12-01", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Interactive Screen-Space Triangulation for High-Quality Rendering of Point Clouds", "date": "2012-04", "abstract": "This technical report documents work that is a precursor to the Auto Splatting technique. We present a rendering method that reconstructs high quality images from unorganized colored point data. While previous real-time image reconstruction approaches for point clouds make use of preprocessed data like point radii or normal estimations, our algorithm only requires position and color data as input and produces a reconstructed color image, normal map and depth map which can instantly be used to apply further deferred lighting passes. Our method performs a world-space neighbor search\nand a subsequent normal estimation in screen-space, and uses the geometry shader to triangulate the color, normal\nand depth information of the points. To achieve correct visibility and closed surfaces in the projected image a temporal coherence approach reuses triangulated depth information and provides adaptive neighbor search radii. Our algorithm is especially suitable for insitu high-quality visualization of big datasets like 3D-scans, making otherwise time-consuming preprocessing steps to reconstruct surface normals or point radii dispensable.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 747, "image_height": 518, "name": "TR-186-2-12-01-.png", "type": "image/png", "size": 429373, "path": "Publication:TR-186-2-12-01", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799, 193 ], "number": "TR-186-2-12-01", "research_areas": [ "Rendering" ], "keywords": [ "screen triangulation", "point rendering", "nearest neighbors", "screen-space", "point clouds" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 747, "image_height": 518, "name": "TR-186-2-12-01-.png", "type": "image/png", "size": 429373, "path": "Publication:TR-186-2-12-01", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-:thumb{{size}}.png" }, { "description": null, "filetitle": "tech-report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "TR-186-2-12-01-tech-report.pdf", "type": "application/pdf", "size": 8849194, "path": "Publication:TR-186-2-12-01", "url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-tech-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/TR-186-2-12-01-tech-report:thumb{{size}}.png" } ], "projects_workgroups": [ "TERAPOINTS" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2012/TR-186-2-12-01/", "__class": "Publication" }, { "id": "preiner11IR", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": "Screen-Space Triangulation for Interactive Point Rendering", "date": "2011-06-06", "abstract": "We present a novel rendering technique that reconstructs high quality images from unorganized colored point data. While previous point rendering approaches make mostly use of preprocessed point normals and radii, our algorithm only requires position and color data as input and produces a reconstructed color image, normal map and depth map which can instantly be used to apply further deferred lighting passes. \nOur method performs a world-space neighbor search and a subsequent normal estimation in screen-space, and uses the geometry shader to triangulate the color, normal and depth information of the points. To achieve correct visibility and closed surfaces in the projected image a temporal coherence approach reuses triangulated depth information and provides adaptive neighbor search radii. Our algorithm is especially suitable for in-situ high-quality visualization of big datasets like 3D-scans, making otherwise time-consuming preprocessing steps to reconstruct surface normals and point radii dispensable.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 809, "image_height": 574, "name": "preiner11IR-.png", "type": "image/png", "size": 567107, "path": "Publication:preiner11IR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799 ], "date_from": "2011-06-06", "date_to": "2011-06-09", "event": "Austrian-Russian Joint Seminar", "lecturer": [ 799 ], "location": "Vienna", "research_areas": [ "Rendering" ], "keywords": [ "point visualization", "screen space reconstruction" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 809, "image_height": 574, "name": "preiner11IR-.png", "type": "image/png", "size": 567107, "path": "Publication:preiner11IR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-:thumb{{size}}.png" }, { "description": null, "filetitle": "slides", "main_file": true, "use_in_gallery": false, "access": "public", "name": "preiner11IR-slides.pdf", "type": "application/pdf", "size": 2978755, "path": "Publication:preiner11IR", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-slides.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/preiner11IR-slides:thumb{{size}}.png" } ], "projects_workgroups": [ "TERAPOINTS" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/preiner11IR/", "__class": "Publication" }, { "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": [ 799 ], "supervisor": [ 193 ], "research_areas": [], "keywords": [ "mirror space", "interactive reflections", "curved mirrors", "point clouds" ], "weblinks": [], "files": [ { "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" }, { "description": "", "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pr10-poster.pdf", "type": "application/pdf", "size": 1047526, "path": "Publication:pr10", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-poster:thumb{{size}}.png" }, { "description": "", "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pr10-thesis.pdf", "type": "application/pdf", "size": 13005654, "path": "Publication:pr10", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/pr10-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "Scanopy" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2010/pr10/", "__class": "Publication" }, { "id": "preiner_2010_GIPC", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Real-Time Global Illumination for Point Cloud Scenes", "date": "2010", "abstract": "In this paper we present a real-time global illumination approach for illuminating scenes containing large point clouds. Our approach is based on the distribution of Virtual Point Lights (VPLs) in the scene, which are then used for the indirect illumination of the visible surfaces, using Imperfect Shadow Maps for visibility calculation of the VPLs. We are able to render multiple indirect light bounces, where each light bounce accounts for the transport of both the diffuse and the specular fraction of the reflected light.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 831, "image_height": 551, "name": "preiner_2010_GIPC-image.png", "type": "image/png", "size": 322383, "path": "Publication:preiner_2010_GIPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799, 193 ], "journal": "Computer Graphics & Geometry", "number": "1", "pages_from": "2", "pages_to": "16", "volume": "12", "research_areas": [ "Rendering" ], "keywords": [ "virtual point lights", "imperfect shadow maps", "point rendering", "point clouds", "global illumination", "VPL", "ISM" ], "weblinks": [ { "href": "http://www.cgg-journal.com/2010-1/02.htm", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "algorithm", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1684, "image_height": 950, "name": "preiner_2010_GIPC-algorithm.png", "type": "image/png", "size": 1001756, "path": "Publication:preiner_2010_GIPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-algorithm.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-algorithm:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 831, "image_height": 551, "name": "preiner_2010_GIPC-image.png", "type": "image/png", "size": 322383, "path": "Publication:preiner_2010_GIPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-image:thumb{{size}}.png" }, { "description": null, "filetitle": "shots", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2136, "image_height": 478, "name": "preiner_2010_GIPC-shots.png", "type": "image/png", "size": 993581, "path": "Publication:preiner_2010_GIPC", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-shots.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/preiner_2010_GIPC-shots:thumb{{size}}.png" } ], "projects_workgroups": [ "Scanopy" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2010/preiner_2010_GIPC/", "__class": "Publication" }, { "id": "PREINER-2009-GIPC", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Global Illumination for Point Clouds", "date": "2009", "abstract": "", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 799 ], "date_end": "2009-10-08", "date_start": "2009-07-17", "matrikelnr": "0430380", "supervisor": [ 193, 614 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ "Scanopy" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2009/PREINER-2009-GIPC/", "__class": "Publication" } ]