to use noisy, but redundant data from multiple framework streams and incorporate it with the contextual and sensor knowledge that is provided by both the physical domain imposed by the local environment where the constraints results of applying the Bayesian framework to preliminary people localization problem in indoor environment the lots, hospitals, governmental buildings, and parking malls has created many opportunities for shopping security and business applications. Surveillance homeland threat detection, monitoring sensitive areas and for unusual events, tracking customers in retail detecting controlling and monitoring the movement of assets, stores, monitoring elderly and sick people at home are just and of the applications that require the ability to some system built for this task should also be able to robust this sensory data with contextual information and integrate knowledge provided by humans to maintain a domain logical picture of the world over time. While coherent surveillance has been in use for decades, systems that video automatically detect and track people (or objects) in can research area. Many approaches have been proposed active video surveillance in recent years [1-6]. They differ in for aspects such as number of cameras used, type of various (grayscale or color, mono or stereo, CCD or cameras (indoors or outdoors), area covered (a room or environment hall, a hallway, several connected rooms, a parking lot,
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