The project addresses the problem of visual motion analysis by establishing a voting-based computational framework. We present a novel approach for matching and motion capture that recovers the dense velocity field, motion boundaries and regions from a sequence of images, based on a 4-D layered representation of data, and a voting scheme for token affinity communication. We then interpret these layers in order to generate a full dense 3-D structure of the scene, with independently moving objects segmented. Our current work involves extending the formalism to multiple frames, and improving computational efficiency.