An experimental evaluation of linear and kernel-based methods for face recognition

Proceedings of IEEE Workshop on Applications of Computer Vision

Volumn 2002-January, Issue , 2002, Pages 13-18

  Gupta, H ^a   Agrawal, A K ^a   Pruthi, T ^a   Shekhar, C ^a   Chellappa, R ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

Data mining; Face recognition; Feature extraction; Image databases; Kernel; Linear discriminant analysis; Neural networks; Principal component analysis; Support vector machine classification; Support vector machines

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; DATA MINING; DISCRIMINANT ANALYSIS; FACE RECOGNITION; FEATURE EXTRACTION; IMAGE RETRIEVAL; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

DIMENSIONALITY REDUCTION; DIMENSIONALITY REDUCTION TECHNIQUES; IMAGE DATABASE; KERNEL; KERNEL DISCRIMINANT ANALYSIS; KERNEL PRINCIPAL COMPONENT ANALYSES (KPCA); LINEAR DISCRIMINANT ANALYSIS; SUPPORT VECTOR MACHINE CLASSIFICATION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84921726711     PISSN: 21583978     EISSN: 21583986     Source Type: Conference Proceeding    
DOI: 10.1109/ACV.2002.1182137     Document Type: Conference Paper

References (18)

1. B.S. Manjunath, R. Chellappa, C. von der Malsburg, "A Feature Based Approach to Face Recognition", in Proceedings, IEEE Conference on Computer Vision and Pattern Recognition, pp.373-378, 1992.
2. Kwang In Kim, Keechul Jung and Hang Joon Kim, "Face Recognition Using Kernel Principal Component Analysis", IEEE Signal Processing letters, Vol 9, No. 2, Feb 2002.
3. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Klaus-Robert Müller, "Fisher Discriminant Analysis With Kernels", Neural Networks for Signal Processing IX, 1999
4. Bernhard Scholkpof, Alexander Smola, and Klaus-Robert Muller, "Nonlinear Component Analysis as a kernel Eigenvalue Problem", Tubingen, Germany, Tech. Report No 44, Dec 1996.
5. Christopher J C Burges, "A Tutorial on Support Vector Machines for Pattern Recognition", Bell Laboratories, Lucent Technologies, 1998.
6. T. Joachims, "Making large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning", B. Schölkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999.
7. W. Y. Zhao, R. Chellappa, A. Rosenfeld, and P. J. Phillips, "Face recognition: A literature survey", UMD CfAR Technical Report CAR-TR-948, 2000.
8. M.Turk and A.Pentland, "Eigenfaces for recognition", Journal of Cognitive Neuroscience, 3(1):71-86,1991.
9. UMIST Face Database, UK. URL: http://images.ee.umist.ac.uk/danny/database.html.
10. K.Etemad and R.Chellappa, "Discriminant Analysis for recognition of human face images", Journal of the Optical Society of America A,14(8):1724-1733, 1997.
11. V.Vapnik, The Nature of Statistical Learning Theory, Springer-Verlag, NY, 1995.
12. G.D Guo, S.Z.Li, and K.L. Chan, "Face recognition by Support Vector Machines", Proc. Int. Conf. Automatic Face and Gesture Recognition, pp.196-201, 2000.
13. Yang, M. H., "Kernel EigenFaces vs Kernel Fisherfaces: Face Recognition using Kernel Methods", Proc. of the Fifth Int. Conf. on Automatic Face and Gesture Recognition, pp215-220, May 2002.
14. light software,URL: http://svmlight.joachims.org.
15. L. Sirovich, M. Kirby, "Low dimensional procedure for the characterization of human faces", Journal of Optical Society of America, Vol.4, No.3, pp.519-524, 1987.
16. L. Wiskott, J..M. Fellous, C. von der Malsburg, "Face Recognition by Elastic Bunch Graph Matching", IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 19, pp. 775-779, 1997.
17. P.N Belhumeur, D.J Kriegman, J.P. Hespanha, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection", IEEE Conference on Pattern Analysis and Machine Intelligence, Vol. 19, pp. 711-720, 1997.
18. Daniel B. Graham, Nigel M. Allinson, "Face Recognition: From Theory to Applications", NATO ASI Series F, Computer and Systems Sciences, Vol. 163, pp. 446-456, 1998.