Hybrid recursive energy-based method for robust optical flow on large motion fields

Abstract

We present a new reliable hybrid recursive method for optical flow estimation. The method efficiently combines the advantage of discrete motion estimation and optical flow estimation in a recursive block-to-pixel estimation scheme. Integrated local and global approaches using the robust statistic of anisotropic diffusion remove outliers from the estimated motion field. We separately describe the process with two frameworks i.e. an incremental updating framework and a robust energy minimization framework. With robust error norms of Perona and Marik anisotropic diffusion, the formulation usually leads to non-convex optimization problems. Thus, the solution has many local minima, and convergence to the global minima is not guaranteed. Our hybrid recursive energy-based method employs a hierarchical block-to-pixel estimation concept to prevent this problem. The experimental results prove the excellent performance on several large motion fields.