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Published in:
2011 | OriginalPaper | Chapter
Bayesian Loop for Synergistic Change Detection and Tracking
Authors : Samuele Salti, Alessandro Lanza, Luigi Di Stefano
Published in: Computer Vision – ACCV 2010 Workshops
Publisher: Springer Berlin Heidelberg
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In this paper we investigate Bayesian visual tracking based on change detection. Although in many proposals change detection is key for tracking, little attention has been paid to sound modeling of the interaction between the change detector and the tracker. In this work, we develop a principled framework whereby both processes can virtuously influence each other according to a Bayesian loop: change detection provides a completely specified observation likelihood to the tracker and the tracker provides an informative prior to the change detector.