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Gi Beom Lee, Moonsoo Jeong, Yechan Seok, and Sungkil Lee

Computer Graphics Forum (Proc. Eurographics'21), 40(2), 489–495, 2021.
Presented at Eurographics 2021, Vienna, Austria (Virtual Conference)
Abstract
This paper presents a scalable online occlusion culling algorithm, which significantly improves the previous raster occlusion culling using object-level bounding volume hierarchy. Given occluders found with temporal coherence, we find and rasterize coarse groups of potential occludees in the hierarchy. Within the rasterized bounds, per-pixel ray casting tests fine-grained visibilities of every individual occludees. We further propose acceleration techniques including the read-back of counters for tightly-packed multidrawing and occluder filtering. Our solution requires only constant draw calls for batch occlusion tests, while avoiding costly iteration for hierarchy traversal. Our experiments prove our solution outperforms the existing solutions in terms of scalability, culling efficiency, and occlusion-query performance.
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Bibliography
@ARTICLE{lee21:hroc, title={{Hierarchical Raster Occlusion Culling}}, author={Gi Beom Lee and Moonsoo Jeong and Yechan Seok and Sungkil Lee}, journal={{Computer Graphics Forum (Proc. Eurographics'21)}}, volume={40}, number={2}, pages={489--495}, year={2021} }




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