Information
- Publication Type: Journal Paper with Conference Talk
- Workgroup(s)/Project(s):
- Date: May 2020
- Journal: Computer Graphics Forum
- Volume: 39
- Number: 2
- Location: Norköpping, Sweden
- Lecturer: Markus Schütz
- ISSN: 1467-8659
- Event: EUROGRAPHICS 2020
- DOI: 10.1111/cgf.13911
- Call for Papers: Call for Paper
- Booktitle: EUROGRAPHICS
- Pages: 14
- Publisher: John Wiley & Sons Ltd.
- Conference date: 25. May 2020 – 29. May 2020
- Pages: 51 – 64
- Keywords: point-based rendering
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.We 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.
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- DOI: 10.1111/cgf.13911
BibTeX
@article{schuetz-2020-PPC, title = "Progressive Real-Time Rendering of One Billion Points Without Hierarchical Acceleration Structures", author = "Markus Sch\"{u}tz and Gottfried Mandlburger and Johannes Otepka and Michael Wimmer", year = "2020", 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. We 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. ", month = may, journal = "Computer Graphics Forum", volume = "39", number = "2", issn = "1467-8659", doi = "10.1111/cgf.13911", booktitle = "EUROGRAPHICS", pages = "14", publisher = "John Wiley & Sons Ltd.", pages = "51--64", keywords = "point-based rendering", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/schuetz-2020-PPC/", }