Yang J, Zhang D, and Alejandro F, et al.. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2004, 26(1): 131-137.[2] Rajkiran G and Asari V K. An improved face recognition technique based on modular PCA approach. Pattern Recognition Letters, 2004, 25(4): 429-436.[3] Zuo Wang-meng, Zhang D, and Wang Kuan-quan.Bidirectional PCA with assembled matrix distance Metric for image recognition. IEEE Transaction on Systems, Man, and Cybernetics-part B: Cyebrnetics, 2006, 36(4): 863-872.[4] Chen Song-can and Zhu Yu-lian. Subpattern-based principle component analysis. Pattern Recognition, 2004, 37(5): 1081-1083.[5] Tan Ke-ren and Chen Song-can. Adaptively weighted sub-pattern PCA for face recognition. Neurocomputing, 2005, 64(1): 505-511.[6] Eftekhari A. Mohamad Forouzanfar and Hamid Abrishami Moghaddam. Block-wised 2D kernel PCA/LDA for recognition. Information Processing Letters, 2010, 110(17): 761-766.[7] Huang Guo-hong. Fusion (2D)2PCALDA: a new method for face recognition. Applied Mathematics and Computation, 2010, 216(11): 3195-3199.[8] Qi Yong-feng and Zhang Jia-shu. (2D)2PCALDA: an efficient approach for face recognition. Applied Mathematics and Computation, 2009, 213(1): 1-7.[9] Wang Jin, Barret A, and Wang Lu, et al.. Multilinear principal component analysis for face recognition with fewer features. Neurocomputing, 2010, 73(10-12): 1550-1555.[10] Yu W, Wang Z, and Chen W. A new framework to combine vertical and horizontal information for face recognition. Neurocomputing, 2009, 72(4-6): 1084-1091.[11] Zheng Wei-shi, Lai J H, and Li S Z. 1D-LDA vs. 2DLDA: when is vector-based linear discriminant analysis better than matrix-based?. Pattern Recognition, 2008, 41(7): 2156-2172.[12] Belhumeur P N, Hespanha J P, and Kriengman D J. Eigenfacs vs. fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7): 711-720.[13] Yuen P C and Lai J H. Face representation using independent component analysis. Pattern Recognition, 2002, 35(6): 1247-1257.[14] Yang M H. Kernel eigenfaces vs. kernel fisherfaces: face recognition using kernel methods. Proc Fifth IEEE int1 conf. Automatic Face and Gesture Recognition(RGR02), Washinton D C, May 2002: 215-220.
|