Rate-distortion optimized optical flow estimation

We propose a general framework for rate-distortion optimized estimation of optical flow, taking heed of the optimality conditions when both the residue and the motion coefficients are quantized and coded. The framework is particularly well suited for wavelet estimation of motion, where the estimated coefficients can additionally be coded in a scalable fashion. We also give a summary of two majorization-minimization type of optimization algorithms that can be used to solve our non-linear and non-convex rate-distortion optimization problem. We show experimentally that the proposed scheme produces motion descriptions that are superior to those produced by other optical flow algorithms, in the rate and distortion sense.