Abstract. In this paper, we propose a variational framework for computing a superresolved image of a scene from an arbitrary input video. To this end, we employ a recently proposed...
Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Da...
Abstract. Virtually all variational methods for motion estimation regularize the gradient of the flow field, which introduces a bias towards piecewise constant motions in weakly te...
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
We present an approach to parallel variational optical flow computation on standard hardware by domain decomposition. Using an arbitrary partition of the image plane into rectangul...
Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
We present a closed form solution to the problem of segmenting multiple 2-D motion models of the same type directly from the partial derivatives of an image sequence. We introduce...