This work proposes a system to successfully track, identify and tag target objects or individuals in a real time environment. Consider a sequence of cameras installed in an environment or a facility. Through these cameras user can track those intruders who are aware of how the surveillance system operates and are actively trying to avoid getting seen by the surveillance system. This system tracks the movement of any person’s movement and record and maintain that data throughout any facility in which such a solution is deployed. Movement logging of any individual person can also be done if it does not infringe his/her privacy. Design and analysis a distributed algorithm for the optimization of the recognition and mapping of the given subject/subjects on a User Interface. Finally, the performance and robustness of the distributed system is further analyzed through continuously training the algorithm or maybe real time demo.
Design of Real-Time Self-Frame-Rate-Control Foreground Detection for Multiple Camera Surveillance System
