Probability Distributions of Optical Flow
Eero P. Simoncelli, Edward H. Adelson, and David J. Heeger
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.