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Collision Detection Based on Fuzzy Scene Subdivision

  • David MainzerEmail author
  • Gabriel Zachmann
Chapter

Abstract

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.

Keywords

Collision detection Fuzzy clustering Physics-based animation Computer animation Cloth simulation 

Notes

Acknowledgments

The cloth on ball and funnel simulation benchmarks are courtesy of the UNC Dynamic Scene Benchmarks collection and were provided by Naga Govindaraju, Ilknur Kabul, Stephane Redon, and Simon Pabst.

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Copyright information

© Springer Science+Business Media Singapore 2015

Authors and Affiliations

  1. 1.Clausthal UniversityClausthal-ZellerfeldGermany
  2. 2.University of BremenBremenGermany

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