Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition

Marcelo Armengot, Francesc J. Ferri, Wladimiro Díaz

Abstract

This work presents some preliminary results about exploring and proposing new extensions of common vector based subspace methods that have been recently proposed to deal with very high dimensional classification problems. Both the common vector and the discriminant vector approaches are considered. The different dimensionalities of the subspaces that these methods use as intermediate step are considered in different situations and their relation to the generalization ability of each method is analyzed. Comparative experiments using different databases for the face recognition problem are performed to support the main conclusions of the paper.

References

  1. Fukunaga, K.: Introduction to Statistical Pattern Recognition. Academic Press (1990)
  2. Turk, M., Pentland, A.: Eigenfaces for recognition. Journal of Cognitive Neuroscience 3 (1991) 71-86
  3. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 711-720
  4. Chen, L., Liao, H.M., Ko, M., Lin, J., Yu, G.: A new LDA-based face recognition system which can solve the small sample size problem. Pattern Recognition 33 (2000) 1713-1726
  5. Huang, R., Liu, Q., Lu, H., Ma, S.: Solving the small sample size problem of lda. In: 16th International Conference on Pattern Recognition. Volume 3. (2002) 29-32
  6. Gulmezoglu, M.B., Dzhafarov, V., Keskin, M., Barkana, A.: A novel approach to isolated word recognition. IEEE Transactions on Speech and Audio Processing 7 (1999) 620-628
  7. Gulmezoglu, M.B., Dzhafarov, V., Barkana, A.: The common vector approach and its relation to principal component analysis. IEEE Transactions on Speech and Audio Processing 9 (2001) 655 - 662
  8. Cevikalp, H., Neamtu, M., Wilkes, M., Barkana, A.: Discriminative common vectors for face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (2005) 4 - 13
  9. He, Y.H., Zhao, L., Zou, C.R.: Face recognition using common faces method. Pattern Recognition 39 (2006) 2218-2222
  10. Samaria, F., Harter, A.: Parameterisation of a stochastic model for human face identification. In: 2nd IEEE Workshop on Applications of Computer Vision. (1994)
  11. Swets, D., Weng, J.: Using discriminant eigenfeatures for image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 18 (1996) 831-836
  12. Martinez, A., Benavente, R.: The AR face database. Technical Report 24, Computer Vision Center, Barcelona (1998)
Download


Paper Citation


in Harvard Style

Armengot M., J. Ferri F. and Díaz W. (2007). Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition . In Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007) ISBN 978-972-8865-93-1, pages 129-137. DOI: 10.5220/0002432401290137


in Bibtex Style

@conference{pris07,
author={Marcelo Armengot and Francesc J. Ferri and Wladimiro Díaz},
title={Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition},
booktitle={Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)},
year={2007},
pages={129-137},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002432401290137},
isbn={978-972-8865-93-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)
TI - Experiments about the Generalization Ability of Common Vector based Methods for Face Recognition
SN - 978-972-8865-93-1
AU - Armengot M.
AU - J. Ferri F.
AU - Díaz W.
PY - 2007
SP - 129
EP - 137
DO - 10.5220/0002432401290137