Visual module integration for optical flow estimation

A technique to integrate gradient-based and feature-based modules to estimate the optical flow from a pair of images is proposed. The integration strategy is based on a Bayesian approach, where the optical flow is evaluated as the minimizer of a suitable posterior energy function, containing all the gradient and feature information on the problem. The capability of the technique to constrain the displacement in the neighbourhoods of motion discontinuities has been tested.