Image-based collision detection for deformable cloth models

George Baciu, Wingo Sai Keung Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)

Abstract

Modeling the natural interaction of cloth and garments with objects in a 3D environment is currently one of the most computationally demanding tasks. These highly deformable materials are subject to a very large number of contact points in the proximity of other moving objects. Furthermore, cloth objects often fold, roll, and drape within themselves, generating a large number of self-collision areas. The interactive requirements of 3D games and physically driven virtual environments make the cloth collisions and self-collision computations more challenging. By exploiting mathematically well-defined smoothness conditions over smaller patches of deformable surfaces and resorting to image-based collision detection tests, we developed an efficient collision detection method that achieves interactive rates while tracking self-interactions in highly deformable surfaces consisting of a large number of elements. The method makes use of a novel technique for dynamically generating a hierarchy of cloth bounding boxes in order to perform object-level culling and image-based intersection tests using conventional graphics hardware support. An efficient backward voxel-based AABB hierarchy method is proposed to handle deformable surfaces which are highly compressed.
Original languageEnglish
Pages (from-to)649-663
Number of pages15
JournalIEEE Transactions on Visualization and Computer Graphics
Volume10
Issue number6
DOIs
Publication statusPublished - 1 Nov 2004

Keywords

  • Animation
  • Cloth simulation
  • Collision detection
  • Deformable surfaces

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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