TY - GEN
T1 - Robust face recognition using color information
AU - Liu, Zhiming
AU - Liu, Chengjun
PY - 2009
Y1 - 2009
N2 - This paper presents a robust face recognition method using color information with the following three-fold contributions. First, a novel hybrid color space, the RCrQ color space, is constructed out of three different color spaces: the RGB, YCbCrand YIQ color spaces. The RCrQ hybrid color space, whose component images possess complementary characteristics, enhances the discriminating power for face recognition. Second, three effective image encoding methods are proposed for the component images in the RCrQ hybrid color space: (i) a patch-based Gabor image representation for the R component image, (ii) a multi-resolution LBP feature fusion scheme for the Cr component image, and (iii) a component-based DCT multiple face encoding for the Q component image. Finally, at the decision level, the similarity matrices generated using the three component images in the RCrQ hybrid color space are fused using a weighted sum rule. The most challenging Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 shows that the proposed method, which achieves the face verification rate of 92.43% at the false accept rate of 0.1%, performs better than the state-of-the-art face recognition methods
AB - This paper presents a robust face recognition method using color information with the following three-fold contributions. First, a novel hybrid color space, the RCrQ color space, is constructed out of three different color spaces: the RGB, YCbCrand YIQ color spaces. The RCrQ hybrid color space, whose component images possess complementary characteristics, enhances the discriminating power for face recognition. Second, three effective image encoding methods are proposed for the component images in the RCrQ hybrid color space: (i) a patch-based Gabor image representation for the R component image, (ii) a multi-resolution LBP feature fusion scheme for the Cr component image, and (iii) a component-based DCT multiple face encoding for the Q component image. Finally, at the decision level, the similarity matrices generated using the three component images in the RCrQ hybrid color space are fused using a weighted sum rule. The most challenging Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 shows that the proposed method, which achieves the face verification rate of 92.43% at the false accept rate of 0.1%, performs better than the state-of-the-art face recognition methods
UR - http://www.scopus.com/inward/record.url?scp=69949181254&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=69949181254&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-01793-3_13
DO - 10.1007/978-3-642-01793-3_13
M3 - Conference contribution
AN - SCOPUS:69949181254
SN - 3642017924
SN - 9783642017926
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 122
EP - 131
BT - Advances in Biometrics - Third International Conference, ICB 2009, Proceedings
T2 - 3rd International Conference on Advances in Biometrics, ICB 2009
Y2 - 2 June 2009 through 5 June 2009
ER -