Mean-shift based mixture model for face detection in color image
Human face detection is a challenging task under different lighting conditions. We propose an efficient and reliable algorithm to detect human faces in an image. Our algorithm uses a region-based approach to identify skin-colored pixels under various lighting conditions. Within the detected skin-color regions, a ratio method is proposed to determine possible eye candidates. Two eye candidates form a possible face region, which is then verified by means of a two-stage procedure with an eigenmask. Experimental results based on the HHI MPEG-7 face database show that this face detection algorithm is efficient and reliable under different lighting conditions.