A conditional mixture of neural networks for face detection, applied to locating and tracking an individual speaker

Abstract

We present a neural network approach to human face detection. Using a modular system, a conditional mixture of networks, we are able to detect front view faces as well as turned faces (up to 50 degrees) with excellent performances. This modular network is integrated into LISTEN, our face tracking system. It enables this system to detect and track in real-time faces in a variety of orientations, extending its previous applicability.