VirtualVoxelCrowd: Rendering One Billion Characters at Real-Time
| dc.contributor.author | Yang, Jinyuan | en_US |
| dc.contributor.author | Campbell, Abraham G. | en_US |
| dc.contributor.editor | Liu, Lingjie | en_US |
| dc.contributor.editor | Averkiou, Melinos | en_US |
| dc.date.accessioned | 2024-04-30T08:21:06Z | |
| dc.date.available | 2024-04-30T08:21:06Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In this paper, we introduce VirtualVoxelCrowd, which aims to address the challenges of data scale and overdraw in massive crowd rendering applications. The approach leverages multiple levels of detail and multi-pass culling to reduce rendering workload and overdraw. VirtualVoxelCrowd supports rendering of up to one billion characters, achieving unprecedented scale on standard graphics hardware while rendering subpixel-level voxels to prevent the level of detail transition artifacts. This method offers significant improvements in handling massive animated crowd visualization, establishing a new possibility for dynamic, large-scale scene rendering. | en_US |
| dc.description.sectionheaders | Posters | |
| dc.description.seriesinformation | Eurographics 2024 - Posters | |
| dc.identifier.doi | 10.2312/egp.20241040 | |
| dc.identifier.isbn | 978-3-03868-239-4 | |
| dc.identifier.issn | 1017-4656 | |
| dc.identifier.pages | 2 pages | |
| dc.identifier.uri | https://doi.org/10.2312/egp.20241040 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.2312/egp20241040 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | CCS Concepts: Computing methodologies → Rasterization | |
| dc.subject | Computing methodologies → Rasterization | |
| dc.title | VirtualVoxelCrowd: Rendering One Billion Characters at Real-Time | en_US |