A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
We introduce a probabilistic formalism subsuming Markov random fields of bounded tree width and probabilistic context free grammars. Our models are based on a representation of Bo...
David A. McAllester, Michael Collins, Fernando Per...
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
We propose a novel statistical method for motion detection and background maintenance for a mobile observer. Our method is based on global motion estimation and statistical backgro...
We propose an algorithm for estimating disparity and occlusion in stereo video sequences. The algorithm defines a prior on sequences of disparity maps using a 3D Markov random fie...
Oliver M. C. Williams, Michael Isard, John MacCorm...