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In this paper, an energy minimization method is proposed to estimate the optical flow of an image sequence in the presence of non-uniform illumination variations. The energy function is formulated by combining a data constraint energy that considers the illumination variations and a smoothness constraint, which minimizes the pixel-to-pixel variation of the velocity and illumination fields. Minimization of this energy function is equivalent to solving a linear system, which is accomplished by using an incomplete Cholesky preconditioned conjugate gradient algorithm. A dynamic weighting scheme, which considers the statistical properties of estimated optical flow, is also combined with this algorithm to improve the robustness of our algorithm. This algorithm has been successfully applied to synthetic and real image sequences and some experimental results demonstrate that this algorithm can estimate the optical flow under non-uniform illumination variations accurately.
Pattern Recognition, 2002. Proceedings. 16th International Conference on (Volume:1 )
Date of Conference: 2002