M. Chandrajit

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Motion segmentation is an important task in video surveillance and in many high level vision applications. In this paper, an adaptive method using statistics in temporal framework to segment moving objects from surveillance video sequences captured in dynamic environment is proposed. The proposed method first preprocesses the input frames of video using(More)
Tracking of motion objects in the surveillance videos is useful for the monitoring and analysis. The performance of the surveillance system will deteriorate when shadows are detected as moving objects. Therefore, shadow detection and elimination usually benefits the next stages. To overcome this issue, a method for detection and elimination of shadows is(More)
Multiple objects tracking finds its applications in many high level vision analysis like object behaviour interpretation and gait recognition. In this paper, a feature based method to track the multiple moving objects in surveillance video sequence is proposed. Object tracking is done by extracting the color and Hu moments features from the motion segmented(More)
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