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dc.contributor.authorSimon Pabsten_US
dc.contributor.authorArtur Kochen_US
dc.contributor.authorWolfgang Strasseren_US
dc.date.accessioned2015-02-23T17:15:35Z
dc.date.available2015-02-23T17:15:35Z
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/10.2312/CGF.v29i5pp1605-1612en_US
dc.identifier.urihttp://hdl.handle.net/10.2312/CGF.v29i5pp1605-1612
dc.description.abstractWe 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.en_US
dc.titleFast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfacesen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.description.number5en_US
dc.identifier.doi10.1111/j.1467-8659.2010.01769.xen_US
dc.identifier.pages1605-1612en_US


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