Title: CDFC: Collision Detection Based on Fuzzy Clustering for Deformable Objects on GPU’s
Authors: Mainzer, David
Zachmann, Gabriel
Citation: WSCG 2013: Poster Proceedings: 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS Association, p. 5-8.
Issue Date: 2013
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
conferenceObject
URI: http://wscg.zcu.cz/WSCG2013/!_2013-WSCG-Poster-Proceedings.pdf
http://hdl.handle.net/11025/10629
ISBN: 978-80-86943-76-3
Keywords: detekce kolizí;fuzzy shlukování;počítačová animace;simulace tkaniny
Keywords in different language: collisions detection;fuzzy clustering;computer animation;cloth simulation
Abstract: We present a novel Collision Detection Based on Fuzzy Clustering for Deformable Objects on GPU’s (CDFC) technique to perform collision queries between rigid and/or deformable models. Our method can handle arbitrary deformations and even discontinuous ones. With our approach, we subdivide the scene into connected but totally independent parts by fuzzy clustering, and therefore, the algorithm is especially well-suited to GPU’s. Our collision detection algorithm processes all computations without the need of a bounding volume hierarchy or any other acceleration data structure. One great advantage of this is that our method can handle the broad phase as well as the narrow phase within one single framework. We can compute inter-object and intra-object collisions of rigid and deformable objects consisting of many tens of thousands of triangles in a few milliseconds on a modern computer. We have evaluated its performance by common benchmarks. In practice, our approach is faster than earlier CPUand/ or GPU-based approaches and as fast as state-of-the-art techniques but even more scalable.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG 2013: Poster Proceedings

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