Multi-view object tracking using sequential belief propagation

Authors:
Wei Du;Justus Piater
Affiliations:
Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Liege, Liege, Belgium;Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Liege, Liege, Belgium
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

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Abstract

Multiple cameras and collaboration between them make possible the integration of information available from multiple views and reduce the uncertainty due to occlusions. This paper presents a novel method for integrating and tracking multi-view observations using bidirectional belief propagation. The method is based on a fully connected graphical model where target states at different views are represented as different but correlated random variables, and image observations at a given view are only associated with the target states at the same view. The tracking processes at different views collaborate with each other by exchanging information using a message passing scheme, which largely avoids propagating wrong information. An efficient sequential belief propagation algorithm is adopted to perform the collaboration and to infer the multi-view target states. We demonstrate the effectiveness of our method on video-surveillance sequences.