For a coexisting and collaborative society that incorporates humans and robots, the detection, tracking, and recognition of human motion are indispensable techniques for a robot to safely and securely interact with humans. The present paper proposes a motion tracking system using distributed network cameras that are placed in a sizeable environment, such as a street or a town. Model-based motion tracking is adopted in this system, and an asynchronous process is invoked for updating motion estimation in each camera individually. A 2D distance map created by the Fast Marching Method is used to estimate human motion in real-time. Experiments demonstrate that human motion while walking among eight distributed cameras is tracked correctly by automatically selecting appropriate cameras.