We propose a learning-based approach for motion boundary detection. Precise localization of motion boundaries is essential for the success of optical fl ow estimation, as motion boundaries correspond to discontinuities of the optical fl ow fi eld. The proposed approach allows to predict motion boundaries, using a structured random forest trained on the ground-truth of the MPI-Sintel dataset.

learning to detect motion boundaries.pdf

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