Sequential particle filtering for conditional density propagation on graphs

Authors:
Pan Pan;Dan Schonfeld
Affiliations:
Fujitsu R&D Center Co., Ltd., Beijing, China;University of Illinois at Chicago, IL
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 4
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Abstract

In this paper, we develop novel solutions for particle filtering on graphs. An exact solution of particle filtering for conditional density propagation on directed cycle-free graphs is performed by a sequential updating scheme in a predetermined order. We also provide an approximate solution for particle filtering on general graphs by splitting the graphs with cycles into multiple directed cycle-free subgraphs. We utilize the proposed solution for distributed multiple object tracking. Experimental results show the improved performance of our method compared with existing methods for multiple object tracking.