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Collision-streams: Fast GPU-based collision detection for deformable models (2011)
| Venue: | In ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games |
| Citations: | 9 - 1 self |
BibTeX
@INPROCEEDINGS{Tang11collision-streams:fast,
author = {Min Tang and Dinesh Manocha and Jiang Lin and Ruofeng Tong},
title = {Collision-streams: Fast GPU-based collision detection for deformable models},
booktitle = {In ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games},
year = {2011},
pages = {63--70}
}
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Abstract
into a funnel and pass through it under the pressure of a ball. This model has 47K vertices, 92K triangles, and a lot of self-collisions. Our novel GPU-based CCD algorithm takes 4:4ms and 10ms per frame to compute all the collisions on a NVIDIA GeForce GTX 480 and a NVIDIA GeForce GTX 285, respectively. We present a fast GPU-based streaming algorithm to perform col-lision queries between deformable models. Our approach is based on hierarchical culling and reduces the computation to generating different streams. We present a novel stream registration method to compact the streams and efficiently compute the potentially col-liding pairs of primitives. We also use a deferred front tracking method to lower the memory overhead. The overall algorithm has been implemented on different GPUs and we have evaluated its per-formance on non-rigid and deformable simulations. We highlight our speedups over prior CPU-based and GPU-based algorithms. In practice, our algorithm can perform inter-object and intra-object computations on models composed of hundreds of thousands of tri-angles in tens of milliseconds. 1
Keyphrases
deformable model gpu-based collision detection nvidia geforce gtx intra-object computation memory overhead different stream col-lision query overall algorithm novel stream registration method gpu-based algorithm col-liding pair novel gpu-based ccd algorithm deferred front hierarchical culling different gpus deformable simulation
