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The Visual Computer

, Volume 31, Issue 4, pp 377–389 | Cite as

Continuous collision detection for deformable objects using permissible clusters

  • Sai-Keung WongEmail author
  • George Baciu
Original Article

Abstract

In this paper, we propose a new data structure to perform continuous collision detection (CCD) for deformable triangular meshes. The critical component of this data structure is permissible clusters. At the preprocessing phase, the triangular meshes are divided into permissible clusters. Then, the features of the triangular meshes are assigned to the permissible clusters. At the runtime phase, the potentially colliding feature pairs are collected and they are processed only once in the elementary processing. Our method has been integrated with a normal cone-based method and compared with other CCD methods. Experimental results show that our method improves the overall performance of CCD for deformable objects.

Keywords

Virtual reality Continuous collision detection Deformable objects Triangle clusters 

Notes

Acknowledgments

We thank the reviewers for their constructive and invaluable comments. The animation data of Cloth and Balls were obtained from the UNC Gamma Group. This work was supported in part by the National Science Council Taiwan under contract number NSC 102-2221-E-009-103-MY2 and Hong Kong RGC GRF grants (PolyU 5101/11E, PolyU 5100/12E and PolyU 5100/13E).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.National Chiao Tung UniversityHsinchuTaiwan, ROC
  2. 2.Hong Kong Polytechnic UniversityKowloonHong Kong

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