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This paper presents a robust visual tracking algorithm by exploiting global and local objectpsilas information under a particle filter tracking framework. The proposed algorithm utilize a two-stage cascade scheme to update the particles within the state space in a coarse to fine manner. At the first stage, the object state is estimated by a coarse search using global color statistics. Then a refined...
Background modeling techniques are important for object detection and tracking in video surveillance. Traditional background subtraction approaches are suffered from problems, such as persistent dynamic backgrounds, quick illumination changes, occlusions, noise etc. In this paper, we address the problem of detection and localization of moving objects in a video stream without apperception of background...
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