Software Rasterization of 2 Billion Points in Real Time

Simple item page
dc.contributor.authorSchütz, Markusen_US
dc.contributor.authorKerbl, Bernharden_US
dc.contributor.authorWimmer, Michaelen_US
dc.contributor.editorJosef Spjuten_US
dc.contributor.editorMarc Stammingeren_US
dc.contributor.editorVictor Zordanen_US
dc.date.accessioned2023-01-23T10:23:43Z
dc.date.available2023-01-23T10:23:43Z
dc.date.issued2022
dc.description.abstractThe accelerated collection of detailed real-world 3D data in the form of ever-larger point clouds is sparking a demand for novel visualization techniques that are capable of rendering billions of point primitives in real-time. We propose a software rasterization pipeline for point clouds that is capable of rendering up to two billion points in real-time (60 FPS) on commodity hardware. Improvements over the state of the art are achieved by batching points, enabling a number of batch-level optimizations before rasterizing them within the same rendering pass. These optimizations include frustum culling, level-of-detail (LOD) rendering, and choosing the appropriate coordinate precision for a given batch of points directly within a compute workgroup. Adaptive coordinate precision, in conjunction with visibility buffers, reduces the required data for the majority of points to just four bytes, making our approach several times faster than the bandwidth-limited state of the art. Furthermore, support for LOD rendering makes our software rasterization approach suitable for rendering arbitrarily large point clouds, and to meet the elevated performance demands of virtual reality applications.en_US
dc.description.number3
dc.description.sectionheadersGraphics Systems
dc.description.seriesinformationProceedings of the ACM on Computer Graphics and Interactive Techniques
dc.description.volume5
dc.identifier.doi10.1145/3543863
dc.identifier.issn2577-6193
dc.identifier.urihttps://doi.org/10.1145/3543863
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3543863
dc.publisherACM Association for Computing Machineryen_US
dc.subjectCCS Concepts: Computing methodologies -> Rasterization Additional Key Words and Phrases: point cloud rendering, rasterization, real-time rendering, virtual reality
dc.subjectComputing methodologies
dc.subjectRasterization Additional Key Words and Phrases
dc.subjectpoint cloud rendering
dc.subjectrasterization
dc.subjectreal
dc.subjecttime rendering
dc.subjectvirtual reality
dc.titleSoftware Rasterization of 2 Billion Points in Real Timeen_US
Files
Collections
High-Performance Graphics 2022