Range Face Segmentation: Face Detection and Segmentation for Authentication in Mobile Device Range Images
R. Findling, F. Wenny, C. Holzmann, R. Mayrhofer - Range Face Segmentation: Face Detection and Segmentation for Authentication in Mobile Device Range Images - Proceedings of the 11th International Conference on Advances in Mobile Computing and Multimedia (MoMM2013), Vienna, Austria, 2013, pp. 260-269
Face detection (finding and segmenting faces of different perspectives in images) is an important task as prerequisite to face recognition. This is especially difficult in the mobile domain, as bad image quality and illumination conditions lead to overall reduced face detection rates. Background information still present in segmented faces and unequally normalized faces further decrease face recognition rates. We present a novel approach to robust single upright face detection and segmentation from different perspectives based on range information. We use range face template matching for finding the face's coarse position and gradient vector flow (GVF) snakes for precisely segmenting faces. We further perform face recognition on segmented faces from the 2013 Hagenberg Stereo Vision Pan Shot Face database to evaluate and compare our approach with previous research. Results indicate that range template matching might be a good approach to finding a single face: in our tests we achieved an error free detection rate and average recognition rates above 98%/96% for color/range images.