Reduced deforming filter culling for fast continuous collision detection

  • Authors:
  • Chen Tang;Sheng Li;Guoping Wang

  • Affiliations:
  • Peking University;Peking University;Peking University

  • Venue:
  • Proceedings of the 17th ACM Symposium on Virtual Reality Software and Technology
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a novel efficient deforming filter culling method for continuous collision detection (CCD) problem performed by dimension reduction in subspace. We present a fast linear filter (1D reduced filter) considering relative motion between primitives. We also provide a conservative and fast planar filter test (2D reduced filter) for self-collision feature pairs considering relative motion between vertex and edge. Filter test in subspace removes large amount of false positives and elementary tests with low cost, and improve the overall performance of collision query. We demonstrate our approach and compare it with previous alternatives in kinds of dynamic scenes. Combined with our linear and planar reduced filter, we observe a magnitude of speed improvement on elementary tests (over 2x) compared against previous ones. Our method keeps stable performance for simulations with large step time.