A Real-Time Head Tracker Supporting Human Computer Interaction

This paper describes a fast and completely automatic algorithm for human face tracking. The tracked face is represented by a weighted histogram. The current histogram is compared to histograms at the particles’ positions. The weight of each particle is determined on the basis of Bhattacharyya distance and intensity gradient along the ellipse’s boundary. The incorporation of information about the distance between the camera and the face undergoing tracking results in robust tracking even in presence of skin colored regions in the background. The initialization of the tracker is realized by means of face detection. The detection is carried out using Haar-like features, followed by the verification of face distance to the camera and face region size heuristics.