Quick-CULLIDE: fast inter- and intra-object collision culling using graphics hardware

Naga K. Govindaraju, Ming C. Lin, Dinesh Manocha
Department of Computer Science, University of North Carolina at Chapel Hill
In SIGGRAPH ’05: ACM SIGGRAPH 2005 Courses (2005)


   title={Quick-cullide: Fast inter-and intra-object collision culling using graphics hardware},

   author={Govindaraju, N.K. and Lin, M.C. and Manocha, D.},

   booktitle={Virtual Reality, 2005. Proceedings. VR 2005. IEEE},






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We present a fast collision culling algorithm for performing inter- and intra-object collision detection among complex models using graphics hardware. Our algorithm is based on CULLIDE and performs visibility queries on the GPUs to eliminate a subset of geometric primitives that are not in close proximity. We present an extension to CULLIDE to perform intra-object or self-collisions between complex models. Furthermore, we describe a novel visibility-based classification scheme to compute potentially-colliding and collision-free subsets of objects and primitives, which considerably improves the culling performance. We have implemented our algorithm on a PC with an NVIDIA GeForce FX 6800 Ultra graphics card and applied it to three complex simulations, each consisting of objects with tens of thousands of triangles. In practice, we are able to compute all the self-collisions for cloth simulation up to image-space precision at interactive rates.
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