Speaker: Francois Faure (University Joseph Fourier, Grenoble)
We present a new framework to efficiently trade off acuracy for speed in collision detection between deformable objects. It combines a conventional proximity detection based on hierarchical bounding volumes with a stochastic method for collision detection. The hierarchical method selects regions of possible collisions. The stochastic method randomly selects pairs of geometric primitives in these regions and make them iteratively converge to local distance minima. By tuning the number of active pairs, a trade-off between complete detection and computation speed is obtained. Preliminary results exhibit significant speedups over previous approaches.