PCA plus F-LDA: A new approach to face recognition

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 21, Issue 6, 2007, Pages 1059-1068

  Wang, Huiyuan ^a   Wang, Zengfeng ^b   Leng, Yan ^c   Wu, Xiaojuan ^a   Li, Qing ^d  

^a SHANDONG UNIVERSITY   (China)

^b LUDONG UNIVERSITY   (China)

^c SHANDONG NORMAL UNIVERSITY   (China)

^d Shandong Meteorological Bureau   (China)

Author keywords

Face recognition; Feature extraction; Fractional step linear discriminant analysis; Linear discriminant analysis; Subspace analysis

Indexed keywords

COMPUTATIONAL METHODS; DATABASE SYSTEMS; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS;

FRACTIONAL-STEP LINEAR DISCRIMINANT ANALYSIS; SUBSPACE ANALYSIS;

FACE RECOGNITION;

EID: 34548774028     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S021800140700579X     Document Type: Article

References (14)

1. P. N. Belhumeur, J. P. Hespanha and D. J. Kriegman, Eigenfaces vs. Fisherfaces; recognition using class specific linear projection, IEEE Trans. Patt. Anal. Mach. Intell. 19 (1997) 711-720.
2. L. F. Chen, H. Y. M. Liao, J. C. Lin, M. D. Kao and G. J. Yu, A new LDA-based face recognition system which can solve the small sample size problem, Patt. Recogn. 33(10) (2000) 1713-1726.
3. D. B. Graham and N. M. Allinson, Characterizing virtual eigensignatures for general purpose face recognition, Face Recognition: From Theory to Applications, NATO ASI Series F, Computer and Systems Sciences, Vol. 163, eds. H. Wechsler, P. J. Phillips, V. Bruce, F. Fogelman-Soulie and T. S. Huang (1998), pp. 446-456.
4. R. Huang, et al., Solving the small sample size problem of LDA, Proc. 16th Int. Conf. Pattern Recognition, Quebec, Canada (August 2002), pp. 29-32.
5. C. J. Liu and H. Wechsler, A shape- and texture-based enhanced Fisher classifier for face recognition, IEEE Irans. Imag. Process. 10(4) (2001) 598-608.
6. M. Loog and R. P. W. Dulin, Multiclass linear dimension reduction by weighted pairwise Fisher criteria, IEEE Trans. Patt. Anal. Mach. Intell. 23 (2001) 762-766.
7. R. Lotlikar and R. Kothari, Fractional-step dimensionality reduction, IEEE Trans. Patt. Anal. Mach. Intell. 22 (2000) 623-627.
8. A. M. Martinez and R. Enavente, The AR database, CVC Technical Report 24, June 1998.
9. D. L. Swets and J. J. Weng, Using discriminant eigenfeatures for image retrieval, IEEE Trans. Patt. Anal. Mach. Intell. 18(8) (1996) 831-836.
10. M. Turk and A. Pentland, Eigenfaces for recognition, J. Cogn. Neurosci. 3 (1991) 71-86.
11. J. Yang and J. Y. Yang, Why can LDA be performed in PCA transformed space? Patt. Recogn. 36(2) (2003) 563-566.
12. 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. Patt. Anal. Mach. Intell. 26(1) (2004) 131-137.
13. J. Yang, D. Zhang, X. Yong and J.-Y. Yang, Two-dimensional discriminant transform for face recognition, Patt. Recogn. 38(7) (2005) 1125-1129.
14. H. Yu and J. Yang, A direct LDA algorithm for high-dimensional data - with application to face recognition, Patt. Recogn. 34(10) (2001) 2067-2070.