Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces
Simon Pabst, Artur Koch, Wolfgang Straßer
Eurographics Symposium on Geometry Processing, 2010, pp. 1605--1612.
Abstract: We present a new hybrid CPU/GPU collision detection technique for rigid and deformable objects based on spatial subdivision. Our approach efficiently exploits the massive computational capabilities of modern CPUs and GPUs commonly found in off-the-shelf computer systems. The algorithm is specifically tailored to be highly scalable on both the CPU and the GPU sides. We can compute discrete and continuous external and self-collisions of nonpenetrating rigid and deformable objects consisting of many tens of thousands of triangles in a few milliseconds on a modern PC. Our approach is orders of magnitude faster than earlier CPU-based approaches and up to twice as fast as the most recent GPU-based techniques.
Article URL: http://diglib.eg.org/EG/CGF/volume29/issue5/v29i5pp1605-1612.pdf
BibTeX format:
@inproceedings{Pabst:2010:FAS,
  author = {Simon Pabst and Artur Koch and Wolfgang Straßer},
  title = {Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces},
  booktitle = {Eurographics Symposium on Geometry Processing},
  pages = {1605--1612},
  year = {2010},
}
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