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An Adaptive Object Tracking Using Kalman Filter and Probability Product Kernel
We present a new method for object tracking; we use an efficient local search scheme based on the Kalman filter and the probability product kernel (KFPPK) to find the image regionwith a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed system.
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