Object Tracking in Video Sequence based on Kalman filter
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Abstract
Object tracking has been a hot topic in the area of computer vision. In this paper, a new video moving object tracking method based on Kalman filter is proposed. In initialization, a moving object selected by the user is segmented and the dominant color is extracted from the segmented target. In tracking step, a motion model is constructed to set the system model of adaptive Kalman filter firstly. Then, the dominant color of the moving object in HSI color space will be used as feature to detect the moving object in the consecutive video frames. The detected result is propagated as the measurement of adaptive Kalman filter and the estimate parameters of adaptive Kalman filter are adjusted by occlusion ratio adaptively. Experiments demonstrate that the proposed method is effective video for object tracking applications.
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