We present a real-time face tracker in this paper. The system
has achieved a rate of 30+ frames/second using an HP-9000
workstation with a framegrabber and a Canon VC-C1 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, we 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 search window. Third, a camera model is used to predict
and to compensate for camera motion. The system can
be applied to tele-conferencing 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.