Information theory and face detection

Face detection in complex environments is an unsolved problem which has fundamental importance to face recognition, model based video coding, content based image retrieval, and human computer interaction. In this paper we model the face detection problem using information theory, and formulate information based measures for detecting faces by maximizing the feature class separation. The underlying principle is that search through an image can be viewed as a reduction of uncertainty in the classification of the image. The face detection algorithm is empirically compared using multiple test sets, which include four face databases from three universities.