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A Duality Based Approach For Fractional Order Tv-Model In Optical Flow Estimation

In this paper, a fractional order total variation (TV) model is presented for optical flow estimation in the image sequences. In particular, the proposed model is introduced by generalizing an integer order total variation model formed by using a combination of total variation and quadratic regularization terms. However, it is difficult to solve this minimization problem due to the non-differentiability nature of fractional order TV-term. The fractional order derivative is discretized using the Grünwald-Letnikov derivative. The resulting formulation is solved by using the primal-dual algorithm. The experimental results on different datasets demonstrate the effectiveness of the proposed model against outliers and provide a dense and discontinuity preserving optical flow.