Rotated face detection in color images using radial template (RT)
We propose a face detection algorithm to locate faces rotated in any orientation. Detecting rotated faces is important for a face detection system. First, we present a novel model named radial template (RT) to detect rotated faces. This template is designed to find stable features of center-rotated objects in edge maps. Based on skin detection and edge extraction, our method searches for face-like areas and gets their orientations by RT searching. Then the candidates are rotated upright and a frontal face detector is used to determine the existence of faces. A system integrating these techniques is presented. Experimental results show that our algorithm is effective for detecting human faces rotated at any angle with different sizes, lighting conditions and backgrounds.