There is often a trade-off between the accuracy and the speed of optical flow techniques. Given similar computational resources, this trade-off results in some techniques making i...
Andrew M. Peacock, David S. Renshaw, John M. Hanna...
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...
Reconstruction-based super-resolution from motion video has been an active area of study in computer vision and video analysis. Image alignment is a key component of super-resoluti...
Despite the fact that temporal coherence is undeniably one of the key aspects when processing video data, this concept has hardly been exploited in recent optical flow methods. I...
Sebastian Volz, Andres Bruhn, Levi Valgaerts, Henn...
Illumination inconsistencies cause serious problems for classical computer vision applications such as tracking and stereo matching. We present a new approach to model illuminatio...