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Robust local optical flow: Dense motion vector field interpolation

Optical flow methods integrating sparse point correspondences have made significant contribution in the field of optical flow estimation. Especially for the goal of estimating motion accurately and efficiently, sparse-to-dense interpolation schemes for feature point matches have shown outstanding performances. Concurrently, local optical flow methods have been significantly improved with respect to long-range motion estimation in environments with varying illumination. This motivates us to propose a sparse-to-dense approach based on the Robust Local Optical Flow method. Compared to state-of-the-art methods the proposed approach is significantly faster while retaining competitive accuracy on Middlebury, KITTI 2015 and MPI-Sintel data-set.