By Topic

A non causal Bayesian framework for object tracking and occlusion handling for the synthesis of stereoscopic video

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Moustakas, K. ; Aristotelian Univ. of Thessaloniki, Greece ; Tzovaras, D. ; Strintzis, M.G.

This work presents a framework for the synthesis of stereoscopic video using as input only a monoscopic image sequence. Initially, bi-directional 2D motion estimation is performed, which is followed by an efficient method for the reliable tracking of object contours. Rigid 3D motion and structure is recovered utilizing extended Kalman filtering. Finally, occlusions are dealt with a novel Bayesian framework, which exploits future information to correctly reconstruct occluded areas. Experimental evaluation shows that the layered object scene representation, combined with the proposed methods for object tracking throughout the sequence and occlusion handling, yields very accurate results.

Published in:

3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004. Proceedings. 2nd International Symposium on

Date of Conference:

6-9 Sept. 2004