%0 Journal Article
%T A Bayesian Approach for Segmentation in Stereo Image Sequences
%A Michael G. Strintzis
%A Dimitrios Tzovaras
%A George A. Triantafylllidis
%J EURASIP Journal on Advances in Signal Processing
%D 2002
%I Springer
%R 10.1155/s168761720220606x
%X Stereoscopic image sequence processing has been the focus of considerable attention in recent literature for videoconference applications. A novel Bayesian scheme is proposed in this paper, for the segmentation of a noisy stereoscopic image sequence. More specifically, occlusions and visible foreground and background regions are detected between the left and the right frame while the uncovered-background areas are identified between two successive frames of the sequence. Combined hypotheses are used for the formulation of the Bayes decision rule which employs a single intensity-difference measurement at each pixel. Experimental results illustrating the performance of the proposed technique are presented and evaluated in videoconference applications.
%K Bayesian decision test
%K segmentation
%K stereoscopic video
%K disparity
%K motion.
%U http://dx.doi.org/10.1155/S111086570220606X