Abstract
Moving object tracking plays an important role in applications of object based video conference, video surveillance and so on. The computational complexity is very important in real-time object tracking. We assumed that the background scene is obtained before an object appears in the image and a camera moves after the object is detected. The proposed method can segment an object by using the difference image if there is no camera motion. After camera motion, it can track the object by using the backward BMA (block matching algorithm) with the HFM (human figure model). For real-time tracking, we used the ROI (region of interest) which is the tightest rectangle of the object. The simulation results show that the proposed method efficiently recognizes and tracks the moving camera as well as the fixed camera.
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