Face component detection on the natural office scene

Summary form only given, substantially as follows. This paper describes an automatic face component detection algorithm on the natural office scene. The object image of this algorithm is the front face image of a person seating in a chair at the office. Our algorithm do not use a special capturing environment such as lighting, fixed background and pose. Men seating in a chair sight the camera without any restriction. Namely, the proposed algorithm is able to detect face components from face images under size variation, complex background, and skew angle variation. We have several steps for the face component detection algorithm. The first step is an adaptive sobel edge detection algorithm and the second step is a 2-pass labeling algorithm. The third step is verifications of size, shape and symmetric using face model knowledge for eye detection. The forth step is skew normalization using eye location. The final step is the detection of the mouth and nose.