Computation of Optical Flow Using Dynamic Programming

This paper presents an original algorithm for the computation of optical flow called Orthogonal Dynamic Programming (ODP) as well as several enhancements to it. The principle is to minimize a sum of square differences (SSD) between a pair of images. The originality of the approach is that an optimal matching is searched for entire image strips rather than for pixel neighborhoods. Dynamic programming is used to provide very robust strip alignments and a multiresolution iterative process is used to compute the velocity field. Extensions to the comany intermediate image within the sequence (with non integer image index). Compared to classical methods, this one has the advantage to be able to operate on multi-band (color) images and to provide a dense flow field for the whole image (neither holes nor border shrinks). Continuity and regularity constraints enforced by dynamic programming leads to a very good flow field estimation even in homogeneous or aliased areas.