Intelligent tracking persons through non-overlapping cameras

An intelligent surveillance system can judge and handle a situation automatically within a wide monitoring area and unattended environment that has no certain human supervisor. In this paper, we propose a way to track persons through non-overlapping cameras that are connected over a network with a server. To track persons with a camera and send the tracking data to other cameras, the proposed system uses a human model that comprises a head, a torso, and legs. Also, with a trajectory model, the proposed system can predict the probability which an exited person from one camera is incoming to other cameras. The system is updated online during the lifetime of the system. These enable the proposed to keep tracking the recognized person in a wide area, to provide a guide for monitoring multiple cameras, and to adapt changes with time.