Simple and effective algorithm for automatic tracking of a single object using a pan-tilt-zoom camera
This paper presents a simple but effective algorithm for a pan-tilt-zoom camera to automatically track a single moving object. The proposed tracking algorithm is suitable for but not limited to stationary background, and it can tolerate reasonable noise and light change. The main idea is to initially capture the background information and to calculate the difference between incoming frame and background buffer. Block-based processing is adopted to reduce computation and to alleviate noise effects. Skin-color detection is combined with spatial and temporal information to let the camera more likely to focus on human faces. Even more, the tracking algorithm can be integrated with region-of-interest video coding, which allocates more bits for human faces to produce better subject views. Many practical situations have been tested and the simulation results show that the proposed tracking algorithm is useful for surveillance systems.