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Application of Support Vector Machines in automatic human face recognition

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the possibilities of applying the Support Vector Machines (SVM) in the process of automatic human face recognition. It is described how the existing methods of face recognition can be improved by the SVM. Moreover, a new approach to the multi-method fusion utilising the SVM is proposed. Usefulness of all the methods described in the paper improving the face recognition effectiveness by the SVM is confirmed by the experimental results.
Rocznik
Tom
Strony
143--150
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
  • Silesian University of Technology, Institute of Computer Science, Akademicka 16, 44-101 Gliwice, Poland
Bibliografia
  • [1] BELHUMEUR P. N., HESPANHA J. P., KRIEGMAN D. J., Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Patt. Anal. Mach. Intell. 19, 711–720, 1997
  • [2] CORTES C., VAPNIK V., Support vector networks. Machine Learning, 20(3):273-297, September 1995.
  • [3] GOLDBERG D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, 1989, Addison-Wesley Publishing Co.
  • [4] GONG S., MCKENNA S. J., PSARROU A., Dynamic Vision From Images to Face Recognition, Imperial College Press 1999.
  • [5] GROTHER P., Face Recognition Vendor Test 2002, Supplemental Report, February 2004, NIST IR 7083.
  • [6] KAWULOK M., Masks and Eigenvectors Weights for Eigenfaces Method Improvement, ICCVG International Conference on Computer Vision and Graphics 2004, Warsaw, September 2004.
  • [7] LI Y., GONG S., LIDDELL H., Support Vector Regression and Classification Based Multi-view Face Detection and Recognition. IEEE International Conference on Face Gesture Recognition, Grenoble France, March 2000.
  • [8] OKADA K., STEFFENS J., MAURER T., HONG H., ELAGIN E., NEVEN H., MALSBURG C., The Bochum/USC Face Recognition System and How it Fared in the FERET Phase III Test, in: Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. F. Soulie, T. S. Huang, Eds. Springer-Verlag, Berlin, Germany, 186–205.
  • [9] PHILLIPS P. J., WECHSLER H., HUANG J., AND RAUSS P., The FERET database and evaluation procedure for face recognition algorithms, Image and Vision Computing J, Vol. 16, No. 5, pp 295-306, 1998.
  • [10] TURK M., PENTLAND A., Face Recognition Using Eigenfaces, in: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1991, p.586 – 591.
  • [11] ZHAO W., CHELLAPPA R., PHILLIPS P. J., ROSENFELD A., Face Recognition: A Literature Survey, Technical Report CARTR-948, Center for Automation Research, University of Maryland, College Park, MD, 2000.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0012-0015
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