An Optimized Framework for Detection and Tracking of Video Objects in Challenging Backgrounds

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Provided by: Academy & Industry Research Collaboration Center
Topic: Software
Format: PDF
Segmentation and tracking are two important aspects in visual surveillance systems. Many barriers such as cluttered background, camera movements, and occlusion make the robust detection and tracking a difficult problem, especially in case of multiple moving objects. Object detection in the presence of camera noise and with variable or unfavourable luminance conditions is still an active area of research. This paper propose a framework which can effectively detect the moving objects and track them despite of occlusion and a priori knowledge of objects in the scene.
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