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Object detection and tracking is one of the important aspect in many video surveillance applications like human activity recognition, patient monitoring, traffic control etc. This task becomes more difficult and challenging in varying illumination, occlusion , outdoor scenes and cluttered environment. We proposed an algorithm which continuously update the background and improves the object detection. Detected object is tracked in the next frames of video and then finally it is classified. The videos which are used contains mainly three types of object viz. Single person, group of persons and vehicle. This type of classification is useful in surveillance systems at different places such as shopping mall, parking slot etc.

Object Detection and Tracking in Dynamically Varying Environment