Skip to main content

ICA Based Face Recognition Robust to Partial Occlusions and Local Distortions

  • Conference paper
Biometric Authentication (ICBA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3072))

Included in the following conference series:

Abstract

We propose a novel method using a perfectly local facial representation based on ICA. We named our method ”LS-ICA method”. In the LS-ICA method, basis images are made from their corresponding ICA basis images simply by removing non-salient regions. The LS-ICA basis images display perfectly local characteristics because they contain only locally salient feature regions. This enables us to effectively realize the idea of ”recognition by parts” for face recognition. Experimental results using AT&T, Harvard, FERET and AR databases show that the recognition performance of the LS-ICA method outperforms that of PCA and ICA methods especially in the cases of facial images that have partial occlusions and local distortions such as changes in facial expression and at low dimensions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Back, K., Draper, B.A., Beveridge, J.R., She, K.: PCA vs ICA: A comparison on the FERET data set. In: Joint Conference on Information Sciences, Durham, N.C. (2002)

    Google Scholar 

  2. Turk, M.A., Pentland, A.P.: Eigenfaces for recognition. Cognitive Neuroscience 3(1), 71–86 (1991)

    Article  Google Scholar 

  3. Bartlett, M.S., Movellan, J.R., Sejnowski, T.J.: Face Recognition by Independent Component Analysis. IEEE Transaction on Neural Networks 13, 1450–1464 (2002)

    Article  Google Scholar 

  4. Hyvarinen, A., Oja, E.: Independent component analysis: a tutorial (1999), http://www.cis.hut.fi/~aapo/papers/IJCNN99_tutorialweb/

  5. Cardoso, J.F.: Infomax and Maximum Likelihood for Source Separation. IEEE Letters on Signal Processing 4, 112–114 (1997)

    Article  Google Scholar 

  6. http://www.uk.research.att.com/facedatabase.html

  7. http://cvc.yale.edu/people/faculty/belhumeur.htm

  8. Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face Recognition Algorithms. Pattern Analysis and Machine Intelligence 22, 1090–1104 (2000)

    Article  Google Scholar 

  9. Martinez, M., Benavente, R.: The AR face database. CVC Tech. Report #24 (1998)

    Google Scholar 

  10. Bartlett, M.S.: Face Image Analysis by Unsupervised Learning. Foreword by T. J. Sejnowski, Kluwer International Series on Engineering and Computer Science. Kluwer Academic Publishers, Boston (2001)

    MATH  Google Scholar 

  11. Pentland, P.: Recognition by parts. In: IEEE Proceedings of the First International Conference on Computer Vision, pp. 612–620 (1987)

    Google Scholar 

  12. Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999)

    Article  Google Scholar 

  13. Bell, J., Sejnowski, T.J.: The independent components of natural scenes are edge filters. Advance in Neural Information Processing Systems 9 (1997)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, J., Choi, J., Yi, J. (2004). ICA Based Face Recognition Robust to Partial Occlusions and Local Distortions. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-25948-0_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22146-3

  • Online ISBN: 978-3-540-25948-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics