Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32468
New Adaptive Linear Discriminante Analysis for Face Recognition with SVM

Authors: Mehdi Ghayoumi


We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.

Keywords: lda, adaptive, svm, face recognition.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1310


[1] L.C. Jain., U. Halici, I. Hayashi and S.B. Lee,"Intelligent Biometric Techniques in Fingerprint and Face Recognition," CRC Press, 1999.
[2] Z. SunG. Bebis and R. Miller, "Object Detection Using Feature Subset Selection," Pattern Recognition, Elsevier, vol. 37, no. 11, pp.2165-2176, 2004.
[3] C .Lee and J. Hong,m "Optimizing Feature Extraction for Multiclass Cases," IEEE International Conference on Computational Cybernetics and Simulations, pp.2545-2548, 1997.
[4] J. Mao and A.K.Jain, "Discriminant Analysis Neural Networks," IEEE International Conference on Neural Networks, San Francisco, pp.300- 305, 1993.
[5] C. Chatterjee, Z. Kang and,V.P. Roychowdhury, "Algorithms for Accelerated Convergence of Adaptive PCA," IEEE Transaction of Neural Networks, vol. 11, no. 2,pp.338-355,2000.
[6] H. Abrishami Moghaddam and Kh. Amiri-Zadeh, "Fast Adaptive Algorithms and Networks for Class-separability Features," Pattern Recognition, vol. 36,pp.1695-1702, 2003.
[7] K Fukunaga, "Introduction to Statistical Pattern Recognition," Academic Press, New York, 2nd edition, 1990.
[8] C. Chatterjee and V.P Roychowdhury, "On Self-Organizing Algorithm and Networks for Class-separability Features," IEEE Transaction of Neural Networks, vol. 8, no. 3,pp.663-678, 1997.
[9] Benveniste, A. M. Metivier and Priouret, P.:Adaptive Algorithms and Stochastic Approximations, Springer, Berlin, (1990)
[10] L. Ljung, "Analysis of recursive stochastic algorithms," IEEE Transaction of Automat. vol. 22, no. 4,pp.551-575, 1997.
[11] S. Georghiades, N. Belhumeur,and D. J. Kriegman,"From few to many: illumination cone models for face recognition under variable lighting and pose," IEEE Transaction of Pattern Anal, Machine Intell, pp.643-660, 2001.