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Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.48618th International Conference on Patt ...
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Hanzi Wang, Monash University, Clayton Vic. 3800, Australia
David Suter, Monash University, Clayton Vic. 3800, Australia
It has been shown that integrating multiple cues will increase the reliability and robustness of a vision system in situations that no single cue is reliable. In this paper, we propose a method by fusing multiple cues (i.e., the color cue and the edge cue). In contrast to previous work, we propose a novel shape similarity measure which includes the spatial distribution of, the number of, and the gradient intensity of the edge points. We integrate this shape similarity measure with our recently proposed SMOG-based color similarity measure in the framework of particle filter (PF). Experimental results demonstrate the high robustness and effectiveness of our method in handling appearance changes, cluttered background, moving camera, and occlusions.
Citation:
Hanzi Wang, David Suter, "Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues," icpr, vol. 4, pp.892-895, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006
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