Motion estimation optimization

Motion estimation is cast as a problem in energy minimization. This is achieved by modeling the displacement field as a Markov random field. The equivalence of a Markov random field and a Gibbs distribution is then used to convert the problem into one of defining an appropriate energy function that describes the motion and any constraints imposed on it. The energy function is then minimized using the mean field annealing algorithm, a technique which finds the global or near-global minima in nonconvex optimization problems. Analysis of the algorithm and experimental results are presented