A Likelihood Distribution based Target Tracking

T. Hayashi, S. Enokida, and T. Ejima (Japan)


Particle Filter, Histogram Feature, Likelihood Distribution,Around Reference, Clustering


We study about an object tracking method based on Histogram Feature and Particle Filter. To continue target tracking, updating of the reference histogram and clarify the separation of target / background is important. In this paper, we use a spatial distribution of particles (likelihood distribution) for updating the reference. And we add a histogram feature near the target (around reference) when likelihood calculation for clarify the separation. Actually, as a result of the experiment about any kinds of videos, we could show good tracking performance.

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