Tracking High Speed Skater by Using Multiple Model

GuoJun Liu, XiangLong Tang

Abstract


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Color-based tracking is a very popular technique for object tracking. However, under varying environmental conditions in video sequences, the existing tracking methods tend to be unreliable for tracking high speed objects. It is possible under such a complex environment that the targets may disappear totally or partially due to occlusion. To over this problem, a novel approach of multiple-color model is proposed in this paper. Different colors extracted from the skater’s head and body are tracked with Kalman filter, respectively. A confidence measure representing the reliability of each color tracking result is presented to guide possible re-detection for continuous tracking. Experimental results show that the proposed approach is very efficient and effective in tracking high-speed skater in real short track sequences.


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Computer and Information Science   ISSN 1913-8989 (Print)   ISSN 1913-8997 (Online)
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