Estimating optical flow from clustered trajectories in velocity-time

Presents a new algorithm for the estimation of optical flow from a monocular sequence of images using clustered trajectories in velocity-time. In the new algorithm, the objects in the scene may exhibit rotation and translation in all three dimensions. In addition, interframe displacement may be large-of the order of many pixels. It is assumed that there is a known upper bound on the magnitudes of the x and y components of interframe displacement. The authors conducted tests to compare the performance of the algorithm with that of two prior algorithms for optical flow estimation. They present the results of these tests. The results suggest that the algorithm is an improvement over prior algorithms in its ability to compute the optical flow field accurately under several commonly encountered scene conditions that have posed problems to earlier algorithms for optical flow estimation