Abstract
This paper presents a novel efficient culling method for continuous collision detection (CCD) problem performed by dimension reduction in subspace. The basic idea is to use a fast one-dimension (1D) reduced filter and a fast two-dimension (2D) reduced filter that remove large amount of false positives and elementary tests between the primitives. The culling method could be combined with other techniques. The algorithm has been implemented and tested on two benchmarks, including cloth-ball simulations and N-body simulations. The results demonstrate that the algorithm can efficiently reduce the number of elementary tests one order of magnitude, and improve the overall performance of collision query about one half.
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