A novel SVM+NDA model for classification with an application to face recognition

Pattern Recognition

Volumn 45, Issue 1, 2012, Pages 66-79

  Khan, N M ^a   Ksantini, R ^b   Ahmad, I S ^b   Boufama, B ^b  

^a RYERSON UNIVERSITY   (Canada)

^b UNIVERSITY OF WINDSOR   (Canada)

Author keywords

Face recognition; Kernel NDA and SVM; Linear discriminant analysis (LDA); Nonparametric discriminant analysis (NDA); Small sample size problem; Support vector machines (SVM)

Indexed keywords

KERNEL NDA AND SVM; LINEAR DISCRIMINANT ANALYSIS; NONPARAMETRIC DISCRIMINANT ANALYSIS (NDA); SMALL SAMPLE SIZE PROBLEMS; SUPPORT VECTOR;

DISCRIMINANT ANALYSIS; IMAGE RETRIEVAL; SUPPORT VECTOR MACHINES; VECTORS;

FACE RECOGNITION;

EID: 80052735710     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2011.05.004     Document Type: Article

References (33)

1. A. Asuncion, D.J. Newman, UCI machine learning repository, University of California, Irvine, School of Information and Computer Sciences, 2007.
2. A. Jain, R. Bolle, S. Pankanti (Eds.), BIOMETRIC - Personal Identification in Networked Society, Kluwer Academic Publishers, London, UK, 1999.
3. A.S. Georghiades, Yale face database, Yale University, Center for Computational Vision and Control, 1997.
4. A.D. Belegundu, and T.R. Chandrupatla Optimization Concepts and Applications in Engineering 1999 Prentice-Hall
5. C. Lee, and D.A. Landgrebe Feature extraction based on decision boundaries IEEE Transactions on Pattern Analysis and Machine Intelligence 15 4 1993 388 400
6. C.H. Park, and H. Park Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition SIAM Journal on Matrix Analysis and Application 27 1 2005 98 102
7. G. Baudat, and B. Anouar Generalized discriminant analysis using kernel approach Neural Computation 2000 2385 2404
8. G. Ratsch, T. Onoda, and K.R. Muller Soft margins for adaboost Machine Learning 42 3 2000 287 320 (Pubitemid 32188795)
9. G.H. Golub, and C.F. Van Loan Matrix Computations third ed. 1996 The John Hopkins University Press
10. H. Yu, and J. Yang A direct LDA algorithm for high-dimensional data with application to face recognition Pattern Recognition 34 2001 2067 2070
11. H.W. Kuhn, and A.W. Tucker Nonlinear programming Proceedings of the Second Berkeley Symposium 1950 481 492
12. J. Xu, X. Zhang, and Y. Li Kernel MSE algorithm: a unified framework for KFD, LS-SVM and KRR Proceedings of the International Joint Conference on Neural Networks vol. 2 2001 1486 1491 (Pubitemid 32805384)
13. J.A.K. Suykens, T.V. Gestel, J.D. Brabanter, B.D. Moor, and J. Vandewalle Least Squares Support Vector Machines 2002 World Scientific Pub. Co.
14. J.J. Weng, Crescepton and SHOSLIF: towards comprehensive visual learning, in: Early Visual Learning, 1996, pp. 183214.
15. K. Fukunaga Introduction to Statistical Pattern Recognition second ed. 2000 Academic Press
16. K. Fukunaga, and L. Hostetler The estimation of the gradient of a density function, with applications in pattern recognition IEEE Transactions on Information Theory 21 1 1975 32 40
17. L. Spacek, Face recognition data, University of Essex, Computer Vision Science Research Projects, 2008.
18. M. Cristianini, and J. Shawe-Taylor An Introduction to Support Vector Machines 2000 Cambridge University Press Cambridge, UK
19. M. Loog, and R.P.W. Duin Linear dimensionality reduction via heteroscedastic extension of LDA: the Chernoff criterion IEEE Transactions on Pattern Analysis and Machine Intelligence 26 6 2004 732 739
20. M. Lyons, S. Akamatsu, M. Kamachi, and J. Gyoba Coding facial expressions with Gabor wavelets Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition 1998 200 205
21. MathWorks ™, 2009.
22. M.J. Lyons, J. Budynek, and S. Akamatsu Automatic classification of single facial images IEEE Transactions on Pattern Analysis and Machine Intelligence 21 12 1999 1357 1362 (Pubitemid 30568926)
23. M.L. Yiu, and N. Mamoulis Iterative projected clustering by subspace mining IEEE Transactions on Knowledge and Data Engineering 17 2 2005 176 189 (Pubitemid 40320177)
24. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman Eigenfaces vs. Fisherfaces: recognition using class specific linear projection IEEE Transactions on Pattern Analysis and Machine Intelligence 19 1997 711 720 (Pubitemid 127762263)
25. R.O. Duda, P.E. Hart, and D.G. Stork Pattern Classification second ed. 2000 Wiley-Interscience
26. S. Mika, G. Ratsch, J. Weston, B. Scholkopf, and K.R. Mullers Fisher discriminant analysis with kernels Proceedings of IEEE Neural Networks for Signal Processing Workshop 1999 41 48 (Pubitemid 30510358)
27. P.K. Shivaswamy, and T. Jebara Maximum relative margin and data-dependent regularization Journal of Machine Learning Research 11 2010 747 788
28. T. Xiong, J. Ye, Q. Li, V. Cherkassky, and R. Janardan Efficient kernel discriminant analysis via QR decomposition Advances in Neural Information Processing Systems vol. 17 2005 1529 1536
29. T. Xiong, and V. Cherkassky A combined SVM and LDA approach for classification Proceedings of the International Joint Conference on Neural Networks 2005 1455 1459 (Pubitemid 44591413)
30. T.F. Coleman, and Y. Li A reflective Newton method for minimizing a quadratic function subject to bounds on some of the variables SIAM Journal on Optimization 6 4 1996 1040 1058
31. T.S. Lim, W.Y. Loh, and Y.S. Shih A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms Machine Learning 40 3 2000 203 228
32. V.N. Vapnik Statistical Learning Theory 1998 John Wiley & Sons New York, USA
33. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery Numerical Recipes: The Art of Scientific Computing third ed. 2007 Cambridge University Press