Fast and reliable collision culling using graphics hardware

  • Authors:
  • Naga K. Govindaraju;Ming C. Lin;Dinesh Manocha

  • Affiliations:
  • University of North Carolina at Chapel Hill;University of North Carolina at Chapel Hill;University of North Carolina at Chapel Hill

  • Venue:
  • Proceedings of the ACM symposium on Virtual reality software and technology
  • Year:
  • 2004

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Abstract

We present a reliable culling algorithm that enables fast and accurate collision detection between triangulated models in a complex environment. Our algorithm performs fast visibility queries on the GPUs for eliminating a subset of primitives that are not in close proximity. To overcome the accuracy problems caused by the limited viewport resolution, we compute the Minkowski sum of each primitive with a sphere and perform reliable 2.5D overlap tests between the primitives. We are able to achieve more effective collision culling as compared to prior object-space culling algorithms. We integrate our culling algorithm with CULLIDE [8] and use it to perform reliable GPU-based collision queries at interactive rates on all types of models, including non-manifold geometry, deformable models, and breaking objects.