Computation of optical flow under non-uniform brightness variations

摘要

In this paper, we present a new motion estimation algorithm that provides accurate optical flow computation under non-uniform brightness variations. The proposed algorithm is based on a regularization formulation that minimizes a combination of a modified data constraint energy and a smoothness measure all over the image domain. The data constraint is derived from the conservation of the Laplacian-of-Gaussian (LoG) filtered image function, which alleviates the problem with the traditional brightness constancy assumption under non-uniform illumination variations. The resulting energy minimization is accomplished by an incomplete Cholesky preconditioned conjugate gradient algorithm. Comparisons of experimental results on benchmarking image sequences by using the proposed algorithm and some of the best existing methods are given to demonstrate its superior performance.