Rotated face detection in color images using Radial Template (RT)

In this paper, 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 get their orientations by RT searching. Then the candidates are rotated upright and a frontal face detector is used to determine existence of faces. A system integrating these techniques is presented. Experimental results show that our algorithm is effective to detect human faces rotated in any angle with different sizes, lighting conditions and backgrounds.