Collision Detection Based on Fuzzy Scene Subdivision

David Mainzer, Gabriel Zachmann
Clausthal University, Germany
International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG), 2013


   title={Collision Detection Based on Fuzzy Scene Subdivision},

   author={Mainzer, David and Zachmann, Gabriel},



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We present a novel approach to perform collision detection queries between rigid and/or deformable models. Our method can handle arbitrary deformations and even discontinuous ones. For this, we subdivide the whole scene with all objects into connected but totally independent parts by a fuzzy clustering algorithm. Following, for every part our algorithm performs a Principal Component Analyses to achieve the best sweep direction for the Sweep-Plane step, which reduces the number of false positives greatly. 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. Our collision detection algorithm works directly on all primitives of the whole scene, which results in a simpler implementation and can be integrated much more easily by other applications. 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.
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