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Real time tracking using an active pan-tilt-zoom network camera

We present here a real time active vision system on a PTZ network camera to track an object of interest. We address two critical issues in this paper. One is the control of the camera through network communication to follow a selected object. The other is to track an arbitrary type of object in real time under conditions of pose, viewpoint and illumination changes. We analyze the difficulties in the control through the network and propose a practical solution for tracking using a PTZ network camera. Moreover, we propose a robust real time tracking approach, which enhances the effectiveness by using complementary features under a two-stage particle filtering framework and a multi-scale mechanism. To improve time performance, the tracking algorithm is implemented as a multi-threaded process in OpenMP. Comparative experiments with state-of-the-art methods demonstrate the efficiency and robustness of our system in various applications such as pedestrian tracking, face tracking, and vehicle tracking.