Abstract
A real-time tracking algorithm for estimating the positions, motions and dimensions of unknown objects in image sequences is presented. Processing is based on the dynamic model of the motion imaging situation and on Kalman filter theory. Experimental results on synthetic and real images demonstrate the applicability of the algorithm to surveillance systems.
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