Two-dimensional linear discriminant analysis of principle component vectors for face recognition

IEICE Transactions on Information and Systems

Volumn E89-D, Issue 7, 2006, Pages 2164-2170

  Sanguansat, Parinya ^a   Asdornwised, Widhyakorn ^a   Jitapunkul, Somchai ^a   Marukatat, Sanparith ^b  

^a CHULALONGKORN UNIVERSITY   (Thailand)

^b NATIONAL ELECTRONICS AND COMPUTER TECHNOLOGY CENTER   (Thailand)

Author keywords

2DPCA+2DLDA; Face recognition; Two dimensional linear discriminant analysis (2DLDA); Two dimensional principle component analysis (2DPCA)

Indexed keywords

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; IMAGE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PROBLEM SOLVING; VECTORS;

2DPCA+2DLDA; SMALL SAMPLE SIZE (SSS) PROBLEM; TWO-DIMENSIONAL LINEAR DISCRIMINANT ANALYSIS (2DLDA); TWO-DIMENSIONAL PRINCIPLE COMPONENT ANALYSIS (2DPCA); YALE FACE DATABASE;

FACE RECOGNITION;

EID: 33747874461     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1093/ietisy/e89-d.7.2164     Document Type: Conference Paper

References (14)

1. L. Sirovich and M. Kirby, "Low-dimensional procedure for characterization of human faces," J. Optical Soc. Am., vol.4, pp.519-524, 1987.
2. M. Turk and A. Pentland, "Eigenfaces for recognition," J. Cognitive Neurosci., vol.3, no.1, pp.71-86, 1991.
3. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman, "Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol.19, no.7, pp.711-720, July 1997.
4. W. Zhao, R. Chellappa, and A. Krishnaswamy, "Discriminant analysis of principle components for face recognition," Japan, IEEE 3rd Inter. Conf. on Automatic Face and Gesture Recognition, pp.336-341, 1998.
5. W. Zhao, R. Chellappa, and N. Nandhakumar, "Empirical performance analysis of linear discriminant classifiers," CVPR, pp. 164-171, IEEE Computer Society, 1998.
6. K. Fukunaga, Introduction to Statistical Pattern Recognition, second ed., Academic Press, 1990.
7. L. Chen, H. Liao, M. Ko, J. Lin, and G. Yu, "A new LDA based face recognition system which can solve the small sample size problem," Pattern Recognit, vol.33, no.10, pp.1713-1726, 2000.
8. J. Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Regularized discriminant analysis for the small sample size problem in face recognition," Pattern Recognit. Lett., vol.24, no. 16, pp.3079-3087, 2003.
9. R. Huang, Q. Liu, H. Lu, and S. Ma, "Solving the small sample size problem of LDA," Pattern Recognit., vol.3, pp.29-32, 2002.
10. J. Yang, D. Zhang, A.F. Frangi, and J.Y. Yang, "Two-dimensional PCA: A new approach to appearance-based face representation and recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol.26, no.1, pp.131-137, Jan. 2004.
11. J. Ye, R. Janardan, and Q. Li, "Two-dimensional linear discriminant analysis," in Advances in Neural Information Processing Systems 17, ed. L.K. Saul, Y. Weiss, and L. Bottou, pp.1569-1576, MIT Press, Cambridge, MA, 2005.
12. J. Yang and J.Y. Yang, "From image vector to matrix: A straightforward image projection technique: IMPCA vs. PCA," Pattern Recognit, vol.35, no.9, pp.1997-1999, 2002.
13. Yale, "The Yale face database," 1997. Available from http://cvc.yale.edu/projects/yalefaces/yalefaces.html
14. ORL, "The ORL face database at the AT&T (Olivetti) research laboratory," 1992. Available from http://www.cl.cam.ac.uk/Research/DTG/ attarchive/facedatabase.html