Parallelized robust multiresolution motion estimation

Abstract

Motion estimation is crucial in domains such as robot vision or image sequence coding. Fast or real time computing is often required but is problematic due to computational complexity. In this paper, an algorithm using multiresolution multigrid Markov random fields is parallelized. Such realizations have already been studied for fine parallelizations on massively parallel machines. The goal of this paper is to achieve a coarse parallelization on a network of workstations, using the Parallel Virtual Machine (PVM) software package.