Is two-dimensional PCA a new technique

Zidonghua Xuebao/Acta Automatica Sinica

Volumn 31, Issue 5, 2005, Pages 782-787

  Wang, Li Wei ^a   Wang, Xiao ^a   Chang, Ming ^a   Feng, Ju Fu ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Block based PCA; Face recognition; PCA; Two dimensional PCA

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; IMAGE PROCESSING; MATRIX ALGEBRA; PRINCIPAL COMPONENT ANALYSIS; TWO DIMENSIONAL; VECTORS;

BLOCK BASED PCA; COMPUTATIONAL COST; DE FACTO STANDARDS; EIGENFACES METHOD; FERET DATABASES; TWO DIMENSIONAL PCA;

FACE RECOGNITION;

EID: 26644470089     PISSN: 02544156     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (19)

1. Kirby M, Sirovich L. Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(1): 103-108
2. Jolliffe I T. Principal Component Analysis. New York, Springer-Verlag, 1986
3. Turk M A, Pentland A P. Face recognition using eigenfaces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Maui Hawaii: IEEE Press, 1991. 586-591.
4. Belhumeur P N, Hespanha J P, Kriegman D J. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7): 711-720
5. Etemad K, Chellappa R. Discriminant analysis for recognition of human face images. Journal of Optical Society of America A, 1997, 14(8): 1724-1733
6. Moghaddam B. Bayesian face recognition. Pattern Recognition, 2000, 13(11): 1771-1782
7. Bell A J, Sejnowski T J. An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 1995, 7(6): 1129-1159
8. Comon P. Independent Component analysis-a new concept? Signal Processing, 1994, 36: 287-314
9. Scholkopf B, Smola A, Muller K R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 1998, 10(5): 1299-1319
10. Mika S, Ratsch G, Weston J, Scholkopf B, Muller K. Fisher discriminant analysis with kernels. Neural Networks for Signal Processing IX, Hu Y H, Larsen J, Wilson E, Douglas D, eds., 1999. 41-48
11. Yang J, Zhang D. Two-dimensional PCA: A new approach to appearance-based face representation and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(1): 131-137
12. Yang J, Yang J Y. From image vector to matrix: a straightforward image projection technique-IMPCA vs. PCA. Pattern Recognition, 2002, 35(9): 1997-1999
13. Samaria F, Young S. HMM-based architecture for face identification. Image and Vision Computing, 1994, 12(8): 537-543
14. Kim M, Kim D, Lee S. Face recognition using the embedded HMM with second-order block-specific observations. Pattern Recognition, 2003, 36(11): 2723-2735
15. Wang L, Wang X, Zhang X, Feng J. The equivalence of two-dimensional PCA to line-based PCA. Pattern Recognition Letters. 2005, 26(1): 57-60
16. AT&T Laboratories Cambridge. http://www.uk.research.att.com/facedatabase.html, 2002
17. Martinez A M, Benavente R. The AR face database. CVC Technical Report #24, 1998
18. http://cvc.yale.edu/projects/yalefaces/yalefaces.html.
19. Phillips P. J, Moon H, Rizvi S. A, Rauss P. J. The FERET evaluation methodology for face-recognition algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(10): 1090-1104