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A Bayesian Approach for Segmentation in Stereo Image Sequences

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.

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Correspondence to George A. Triantafylllidis.

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Triantafylllidis, G.A., Tzovaras, D. & Strintzis, M.G. A Bayesian Approach for Segmentation in Stereo Image Sequences. EURASIP J. Adv. Signal Process. 2002, 940529 (2002). https://doi.org/10.1155/S111086570220606X

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Keywords

  • Bayesian decision test
  • segmentation
  • stereoscopic video
  • disparity
  • motion