Combinatorial optimization problems expressed as Boolean constraint satisfaction problems (BCSPs) arise in several contexts, ranging from the classical unate set-packing problems ...
Subspace segmentation is the task of segmenting data
lying on multiple linear subspaces. Its applications in
computer vision include motion segmentation in video,
structure-from...
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Inference tasks in Markov random fields (MRFs) are closely related to the constraint satisfaction problem (CSP) and its soft generalizations. In particular, MAP inference in MRF i...