Kernel direct discriminant analysis and its theoretical foundation

Pattern Recognition

Volumn 38, Issue 3, 2005, Pages 445-447

  Liang, Zhizheng ^a   Shi, Pengfei ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Face recognition; Feature extraction; Kernel discriminant analysis; QR decomposition

Indexed keywords

ALGORITHMS; DATA REDUCTION; DATABASE SYSTEMS; FACE RECOGNITION; FEATURE EXTRACTION; PERSONNEL TRAINING; PROBLEM SOLVING; THEOREM PROVING;

KERNEL DISCRIMINANT ANALYSIS (KDA); QR DECOMPOSITION; SMALL SAMPLE SIZE PROBLEM (SSSP); THEORETICAL FOUNDATION;

EIGENVALUES AND EIGENFUNCTIONS;

EID: 10044248101     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2004.07.007     Document Type: Article

References (5)

1. B. Scholkopf, A. Smola, K.R. Muller, Nonlinear component analysis as a kernel eigenvalue problem, Neural Comput. 10 (5) (1998) 1299-1319.
2. G. Baudat, F. Anouar, Generalized discriminant analysis using a kernel approach, Neural Comput. 12 (10) (2000) 2385-2404.
3. J. Yang, Z. Jin, J. Yang, D. Zhang, The essence of kernel Fisher discriminant: KPCA plus LDA, Pattern Recogn. 37(10) (2004)2097-2100.
4. Juwei Lu, K.N. Plataniotis, A.N. Venetsanopoulos, Face recognition using kernel direct discriminant analysis algorithms, IEEE Trans. Neural Networks 14 (1) (2003) 117-125.
5. K. Fukunaga, Introduction to Statistical Pattern Recognition, second ed., Academic Press, New York, 1990.