EURASIP Journal on Applied Signal Processing 
Volume 2002 (2002), Issue 10, Pages 1116-1126
doi:10.1155/S111086570220606X

A Bayesian Approach for Segmentation in Stereo Image Sequences

George A. Triantafylllidis,1 Dimitrios Tzovaras,2 and Michael G. Strintzis1,2

 1Information Processing Laboratory, Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, Thessaloniki 54006, Greece
2Informatics and Telematics Institute, 1st Km Thermi-Panorama Road, Thermi-Thessaloniki, 57001, Greece
Received 31 August 2001; Revised 14 May 2002

Abstract

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.