Quadratic discriminant analysis method based on virtual training samples

Zidonghua Xuebao/Acta Automatica Sinica

Volumn 34, Issue 4, 2008, Pages 400-407

  Wang, Wei Dong ^a   Yang, Jing Yu ^b  

^a JIANGSU UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Classifier; Face recognition; Perturbation method; Quadratic discriminant analysis; Small sample size problem; Virtual training samples

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISCRIMINANT ANALYSIS;

PERTURBATION METHOD; QUADRATIC DISCRIMINANT ANALYSIS; REGULARIZED DISCRIMINANT ANALYSIS (RDA); SMALL SAMPLE SIZE PROBLEM; VIRTUAL TRAINING SAMPLES;

FACE RECOGNITION;

EID: 43749115504     PISSN: 02544156     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1004.2008.00400     Document Type: Article

References (16)

1. Fisher R A. The use of multiple measurements in taxonomic problems. Annals Eugen, 1936, 7: 178-188
2. 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 Intellgence, 1997, 19(7): 711-720
3. Liu K, Yang J Y. An efficient algorithm for Foley-Sammon optimal set of discriminant vectors by algebraic method. International Journal of Pattern Recognition and Artificial Intelligence, 1992, 6(5): 817-829
4. Friedman J H. Reguralized discriminant analysis. Journal of the American Statistica Association, 1989, 84(405): 165-175
5. Thomaz C E, Gillies D F, Feitosa R Q. A new covariance estimate for Bayesian classifiers in biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 2004, 14(2): 214-223
6. Marcel S. A symmetric transformation for LDA-based face verification. In: Proceedings of the 6th International Conference on Automatic Face and Gesture Recognition. New York, USA: IEEE, 2004, 207-212
7. Wen J W, Zhao J L, Luo S W, Huang H. Face recognition method based on virtual sample. In: Proceedings of the National Science Foundation under Contract. 2001. 557-562
8. Liu Q S, Lu H Q, Ma S D. Improving kernel Fisher discriminant analysis for face recognition. IEEE Transactions on Circuits and System for Video Technology, 2004, 14(1): 42-49
9. Wang Wei-Dong, Zheng Yu-Jie, Yang Jing-Yu. Optimizing regularized discriminant analysis in virtual training samples. Journal of Computer-aided Design and Computer Graphics, 2006, 18(9): 1327-1331
10. Chen Jie, Chen Xi-Lin, Gao Wen. Face samples expanding based on the GA re-sampling. Journal of Software, 2005, 16(11): 1894-1901
11. Liu Hai-Long, Ding Xiao-Qing. Handwritten Chinese character recognition based on mirror image learning and the compound Mahalanobis function. Journal of Tsinghua University (Science and Technology), 2006, 46(7): 1239-1241
12. Golub G H, Fanlon C F. Matrix Computing. Beijing: Science Press, 2001
13. Sun Ji-Guang. Matrix Perturbation Analysis (Second Edition). Beijing: Science Press, 2001
14. Hong Z Q, Yang J Y. Optimal discriminant plane for a small number of samples and design method of classifier on the plane. Pattern Recognition, 1991, 24(4): 317-324
15. Fukunaga K. Introduction to statistical pattern recognition (Second Edition). New York: Academic Press, 1990
16. Stan Z L, Lu J W. Face recognition using the nearest feature line method. IEEE Transactions on Neural Networks, 1999, 10(2): 439-443