Optical flow estimation requires spatial integration, which essentially poses a grouping question: what points belong to the same motion and what do not. Classical local approache...
We show that differentiation via fitting B-splines to the spatio-temporal intensity data comprising an image sequence provides at least the same and usually better 2D Lucas and Ka...
We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natur...
Recent work on early vision such as image segmentation, image restoration, stereo matching, and optical flow models these problems using Markov Random Fields. Although this formula...
We present an approach to parallel variational optical flow computation by using an arbitrary partition of the image plane and iteratively solving related local variational proble...