A model of collision perception for real-time animation

Abstract

A model of human visual perception of collisions is presented, based on twodimensional measures of eccentricity and separation. The model is validated by performing psychophysical experiments. We demonstrate the feasibility of using this model as the basis for perceptual scheduling of interruptible collision detection in a realtime animation of large numbers of visually homogeneous objects. The user's point of fixation may be either tracked or estimated. By using a priority queue scheduling algorithm, perceived collision inaccuracy was approximately halved. The ideas presented are applicable to other tasks where the processing of fine detail leads to a computational bottleneck.