Face Recognition in Different Subspaces: A Comparative Study

Borut Batagelj, Franc Solina

Abstract

Face recognition is one of the most successful applications of image analysis and understanding and has gained much attention in recent years. Among many approaches to the problem of face recognition, appearance-based subspace analysis still gives the most promising results. In this paper we study the three most popular appearance-based face recognition projection methods (PCA, LDA and ICA). All methods are tested in equal working conditions regarding pre-processing and algorithm implementation on the FERET data set with its standard tests. We also compare the ICA method with its whitening preprocess and find out that there is no significant difference between them. When we compare different projection with different metrics we found out that the LDA+COS combination is the most promising for all tasks. The L1 metric gives the best results in combination with PCA and ICA1, and COS is superior to any other metric when used with LDA and ICA2. Our results are compared to other studies and some discrepancies are pointed out.

References

  1. Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face Recognition: A Literature Survey, ACM Computing Surveys, (2003) 399-458
  2. Solina, F.,Peer, P., Batagelj, B., Juvan, S., Kovac?, J.: Color-Based Face Detection in the ”15 Seconds of Fame” Art Installation, International Conference on Computer Vision / Computer Graphics Collaboration for Model-based Imaging, Rendering, image Analysis and Graphical special Effects MIRAGE'03, (2003) 38-47
  3. Turk, M., Pentland, A.: Eigenfaces for Recognition, Journal of Cognitive Neurosicence, 3(1), 1991, 71-86
  4. Zhao, W., Chellappa, R., Krishnaswamy, A.: Discriminant Analysis of Principal Components for Face Recognition, Proc. of the 3rd IEEE International Conference on Face and Gesture Recognition, FG'98, (1998) 336
  5. Bartlett, M.S., Movellan, J.R., Sejnowski, T.J.: Face Recognition by Independent Component Analysis, IEEE Trans. on Neural Networks, 13(6), (2002) 1450-1464
  6. Draper, B., Baek, K., Bartlett, M.S., Beveridge, J.R.: Recognizing Faces with PCA and ICA, Computer Vision and Image Understanding (Spacial Issue on Face Recognition), 91(1-2), (2003) 115-137
  7. Hyvärinen, A., Oja, E.: Independent component analysis: algorithms and aplications. Neural Networks. 13(4-5) (2000) 411-430
  8. Yang, J., Zhang, D., Yang, J.Y.: Is ICA Significantly Better than PCA for Face Recognition? ICCV. (2005) 198-203
  9. Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face-Recognition Algorithms, IEEE Trans. on Pattern Recognition and Machince Intelligence, 22(10), (2000) 1090-1104
  10. Liu, C., Wechsler, H.: Comparative Assessment of Independent Component Analysis (ICA) for Face Rcognition, Second International Conference on Audio- and Video-based Biometric Person Authentication, (1999) 22-23
  11. Baek, K., Draper, B., Beveridge, J.R., She, K.: PCA vs. ICA: A Comparison on the FERET Data Set, Proc. of the Fourth International Conference on Computer Vision, Pattern Recognition and Image Processing, (8-14), (2002) 824-827
  12. Moghaddam, B.: Principal Manifolds and Probabilistic Subspaces for Visual Recognition, IEEE Trans. on Pattern Analysis and Machine Inteligence, 24(6), 2002 780-788
  13. Beveridge, J.R., She, K., Draper, B., Givens, G.H.: A Nonparametric Statistical Comparison of Principal Component and Linear Discriminant Subspaces for Face Recognition, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, (2001) 535-542
  14. Martinez, A., Kak, A.: PCA versus LDA, IEEE Trans. on Pattern Analysis and Machine Inteligence, 23(2), 2001 228-233
  15. Navarrete, P., Ruiz-del-Solar, J.: Analysis and Comparison of Eigenspace-Based Face Recognition Approaches, International Journal of Pattern Recognition and Artificial Intelligence, 16(7), 2002 817-830
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Paper Citation


in Harvard Style

Batagelj B. and Solina F. (2006). Face Recognition in Different Subspaces: A Comparative Study . In 6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006) ISBN 978-972-8865-55-9, pages 71-80. DOI: 10.5220/0002500200710080


in Bibtex Style

@conference{pris06,
author={Borut Batagelj and Franc Solina},
title={Face Recognition in Different Subspaces: A Comparative Study},
booktitle={6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006)},
year={2006},
pages={71-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002500200710080},
isbn={978-972-8865-55-9},
}


in EndNote Style

TY - CONF
JO - 6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006)
TI - Face Recognition in Different Subspaces: A Comparative Study
SN - 978-972-8865-55-9
AU - Batagelj B.
AU - Solina F.
PY - 2006
SP - 71
EP - 80
DO - 10.5220/0002500200710080