Eyes ´n ears: face detection utilizing audio and video cues

This work investigates the development of a robust and portable teleconferencing system utilizing both audio and video cues. An omnidirectional video sensor is used to provide a view of the entire visual hemisphere thereby providing multiple dynamic views of the participants. Regions of skin are detected using simple statistical methods, along with histogram color models for both skin and non-skin color classes. Skin regions belonging to the same person are grouped together. Using simple geometrical properties, the location of each person´s face in the “real world” is estimated and provided to the audio system as a possible sound source direction. Beamforming and sound detection techniques with a small, compact microphone array allows the audio system to detect and attend to the speech of each participant, thereby reducing unwanted noise and sounds emanating from other locations. The results of experiments conducted in normal, reverberant environments indicate the effectiveness of both the audio and video systems