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CULLIDE: interactive collision detection between complex models in large environments using graphics hardware

Naga K. Govindaraju, Stephane Redon, Ming C. Lin, Dinesh Manocha
Department of Computer Science, University of North Carolina at Chapel Hill, U.S.A.
In HWWS ’03: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware (2003), pp. 25-32

@conference{govindaraju2003cullide,

   title={CULLIDE: Interactive collision detection between complex models in large environments using graphics hardware},

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

   booktitle={Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware},

   pages={25–32},

   isbn={1581137397},

   year={2003},

   organization={Eurographics Association}

}

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We present a novel approach for fast collision detection between multiple deformable and breakable objects in a large environment using graphics hardware. Our algorithm takes into account low bandwidth to and from the graphics cards and computes a potentially colliding set (PCS) using visibility queries. It involves no precomputation and proceeds in multiple stages: PCS computation at an object level and PCS computation at sub-object level, followed by exact collision detection. We use a linear time two-pass rendering algorithm to compute each PCS efficiently. The overall approach makes no assumption about the input primitives or the object’s motion and is directly applicable to all triangulated models. It has been implemented on a PC with NVIDIA GeForce FX 5800 Ultra graphics card and applied to different environments composed of a high number of moving objects with tens of thousands of triangles. It is able to compute all the overlapping primitives between different objects up to image-space resolution in a few milliseconds.
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