Probability Distributions of Optical Flow

Eero P. Simoncelli, Edward H. Adelson, and David J. Heeger

Published in:
IEEE Conference on Computer Vision and Pattern Recognition,
Mauii, Hawaii; June, 1991.
Gradient methods are widely used in the computation of optical flow. We discuss extensions of these methods which compute probability distributions of optical flow. The use of distributions allows representation of the uncertainties inherent in the optical flow computation, facilitating the combination with information from other sources. We compute distributed optical flow for a synthetic image sequence and demonstrate that the probabilistic model accounts for the errors in the flow estimates. We also compute distributed optical flow for a real image sequence.