Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based ...
In this paper, we propose an unsupervised segmentation algorithm for extracting moving objects/regions from compressed video using Markov Random Field (MRF) classification. First,...
We present a new method for blind document bleed through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate pri...