TY - GEN
T1 - Illumination normalization using self-lighting ratios for 3D2D face recognition
AU - Zhao, Xi
AU - Shah, Shishir K.
AU - Kakadiaris, Ioannis A.
PY - 2012
Y1 - 2012
N2 - 3D2D face recognition is beginning to gain attention from the research community. It takes advantage of 3D facial geometry to normalize the head pose and registers it into a canonical 2D space. In this paper, we present a novel illumination normalization approach for 3D2D face recognition which does not require any training or prior knowledge on the type, number, and direction of the lighting sources. Estimated using an image-specific filtering technique in the frequency domain, a self-lighting ratio is employed to suppress illumination differences. Experimental results on the UHDB11 and FRGC databases indicate that the proposed approach improves the performance significantly for face images with large illumination variations.
AB - 3D2D face recognition is beginning to gain attention from the research community. It takes advantage of 3D facial geometry to normalize the head pose and registers it into a canonical 2D space. In this paper, we present a novel illumination normalization approach for 3D2D face recognition which does not require any training or prior knowledge on the type, number, and direction of the lighting sources. Estimated using an image-specific filtering technique in the frequency domain, a self-lighting ratio is employed to suppress illumination differences. Experimental results on the UHDB11 and FRGC databases indicate that the proposed approach improves the performance significantly for face images with large illumination variations.
KW - 3D2D face recognition
KW - Lighting ratio
KW - illumination suppression
UR - http://www.scopus.com/inward/record.url?scp=84867728200&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867728200&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33868-7_22
DO - 10.1007/978-3-642-33868-7_22
M3 - Conference contribution
AN - SCOPUS:84867728200
SN - 9783642338670
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 220
EP - 229
BT - Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PB - Springer-Verlag
T2 - Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
Y2 - 7 October 2012 through 13 October 2012
ER -