Efficient Computation of the Most Probable Motion from Fuzzy Correspondences

An algorithm is presented for finding the most probable image motion between two images from fuzzy point correspondences. In fuzzy correspondence a point in one image is assigned to a region in the other image. Such a region can be line (aperture effect) or a probability matrix. Noise and outliers are always present, and points may come from different motions. The presented algorithm, which uses linear programming, recovers the motion parameters and performs outlier rejection and motion-segmentation at the same time. The linear program computes the global optimum without an initial guess