Hierarchically-constrained optical flow

This paper presents a novel approach to solving optical flow problems using a discrete, tree-structured MRF derived from a hierarchical segmentation of the image. Our method can be used to find globally-optimal matching solutions even for problems involving very large motions. Experiments demonstrate that our approach is competitive on the MPI-Sintel dataset and that it can significantly outperform existing methods on problems involving large motions.