Recently, the pan-tilt-zoom (PTZ) camera is extensively used for surveillance in wide area environments. A current automatic system has been developed to continually track a person with the function of keeping the person centered in the field of view (FOV). Tracking moving objects has long been a key problem in computer vision. It is important in a wide variety of video surveillance applications and has been applied successfully in people's daily life, like human motion analysis, traffic monitoring, market guard, and in-house health care. When multiple cameras are used for tracking, the algorithm can automatically provide an optimal capacity and provide a solution to perform the camera assignment efficiently. This paper investigates the application of automatic methods for tracking individual across cameras via a surveillance network. Our approach is to track the individual and activate the function of surveillance in cameras to achieve seamless tracking with high quality image. We develop an emerging low computational complexity hand-off function that can automatically carry out the camera assignment and hand-off task. In the experiment, with a feasible solution for seamless tracking and real-time surveillance provided, our algorithm can perform the hand-off task efficiently and automatically in multiple active camera surveillance systems.