Open Access

A Bayesian Approach for Segmentation in Stereo Image Sequences

  • George A. Triantafylllidis1Email author,
  • Dimitrios Tzovaras2 and
  • Michael G. Strintzis1, 2
EURASIP Journal on Advances in Signal Processing20022002:940529

DOI: 10.1155/S111086570220606X

Received: 31 August 2001

Published: 22 October 2002


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.


Bayesian decision test segmentation stereoscopic video disparity motion

Authors’ Affiliations

Information Processing Laboratory, Electrical and Computer Engineering Department, Aristotle University of Thessaloniki
Informatics and Telematics Institute


© Triantafylllidis et al. 2002