In this paper, we propose a novel technique to represent and recover optical flow through free form deformations. Such a technique is based on representing the motion field usin...
Abstract. We use a simple yet powerful higher-order conditional random field (CRF) to model optical flow. It consists of a standard photoconsistency cost and a prior on affine mo...
Unbiased and consistent estimates of structure and motion can be obtained by least squares minimization of the differential epipolar constraint. Previous work on this subject does...
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...