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The authors present a real-time face tracker. The system has achieved a rate of 30+ frames/second using an HP-9000 workstation with a frame grabber and a Canon VC-Cl camera. It can track a person's face while the person moves freely (e.g., walks, jumps, sits down and stands up) in a room. Three types of models have been employed in developing the system. First, they present a stochastic model to characterize skin color distributions of human faces. The information provided by the model is sufficient for tracking a human face in various poses and views. This model is adaptable to different people and different lighting conditions in real-time. Second, a motion model is used to estimate image motion and to predict the search window. Third, a camera model is used to predict and compensate for camera motion. The system can be applied to teleconferencing and many HCI applications including lip reading and gaze tracking. The principle in developing this system can be extended to other tracking problems such as tracking the human hand.
Yang et al. (Tue,) studied this question.