RACBVHs : random-accessible compressed bounding volume hierarchies
We present a novel compressed bounding volume hierarchy (BVH) representation, random-accessible compressed bounding volume hierarchies (RACBVHs), for various applications requiring random access on BVHs of massive models. Our RACBVH representation is compact and transparently supports random access...
Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 16(2010), 2 vom: 15. März, Seite 273-86 |
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1. Verfasser: | |
Weitere Verfasser: | , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2010
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Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
Zusammenfassung: | We present a novel compressed bounding volume hierarchy (BVH) representation, random-accessible compressed bounding volume hierarchies (RACBVHs), for various applications requiring random access on BVHs of massive models. Our RACBVH representation is compact and transparently supports random access on the compressed BVHs without decompressing the whole BVH. To support random access on our compressed BVHs, we decompose a BVH into a set of clusters. Each cluster contains consecutive bounding volume (BV) nodes in the original layout of the BVH. Also, each cluster is compressed separately from other clusters and serves as an access point to the RACBVH representation. We provide the general BVH access API to transparently access our RACBVH representation. At runtime, our decompression framework is guaranteed to provide correct BV nodes without decompressing the whole BVH. Also, our method is extended to support parallel random access that can utilize the multicore CPU architecture. Our method can achieve up to a 12:1 compression ratio, and more importantly, can decompress 4.2 M BV nodes ({=}135 {\rm MB}) per second by using a single CPU-core. To highlight the benefits of our approach, we apply our method to two different applications: ray tracing and collision detection. We can improve the runtime performance by more than a factor of 4 as compared to using the uncompressed original data. This improvement is a result of the fast decompression performance and reduced data access time by selectively fetching and decompressing small regions of the compressed BVHs requested by applications |
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Beschreibung: | Date Completed 02.04.2010 Date Revised 15.01.2010 published: Print Citation Status MEDLINE |
ISSN: | 1941-0506 |
DOI: | 10.1109/TVCG.2009.71 |