A hybrid real-time face tracking system

A hybrid real-time face tracker based on both sound and visual cues is presented. Initial talker locations are estimated acoustically from microphone array data while precise local-ization and tracking are derived from image information. A computationally eecient algorithm for face detection via motion analysis is employed to track individual faces at rates up to 30 frames per second. The system is robust to nonlinear source motions, complex backgrounds, varying lighting conditions, and a variety of source-camera depths. While the direct focus of this work is automated video con-ferencing, the face tracking capability has utility to many multimedia and virtual reality applications.