Skip to main content
SpringerLink
Log in

Intelligent Face Recognition Using Feature Averaging

  • Conference paper
Book cover Intelligence and Security Informatics (ISI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3975))

Included in the following conference series:

Abstract

Over the past four years there has been a marginal increase in research on developing advanced information technologies that can be efficiently used for national and international security in our war against terrorism. The list of wanted persons who are still free is getting larger, however, in most cases there is a database containing their face images and this can be used in the development of face recognition systems. A human face is an extremely complex object with features that can vary over time, sometimes very rapidly. This paper presents a fast intelligent face recognition system that uses essential face features averaging and a neural network to identify multi-expression faces. A real life application using this method is implemented on 180 images of 30 persons. Experimental results suggest that this simple but efficient system performs well, thus providing a fast intelligent system for recognizing faces with different expressions.

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

Access this chapter

Log in via an institution
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. Li, S.Z., Jain, A.K. (eds.): Handbook of Face Rqecognition. Springer, New York (2005)

    Google Scholar 

  2. Brunelli, R., Poggio, T.: Face Recognition: Features versus Templates. IEEE Transactions on Pattern Analysis and Machine Intelligence 15, 1042–1052 (1993)

    Article  Google Scholar 

  3. Turk, M., Pentland, A.: Eignefaces for Recognition. Journal of Cognitive Neuroscience 3, 72–86 (1991)

    Article  Google Scholar 

  4. Belhumeur, P., Hespanha, J., Kriegman, D.: Eigenfaces vs. Fisherfaces: Face Recognition using class specific linear projection. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1064, pp. 45–58. Springer, Heidelberg (1996)

    Chapter  Google Scholar 

  5. Vasilescu, M.A.O., Terzopoulos, D.: Multilinear Image Analysis for Facial Recognition. In: Proceedings of International Conference on Pattern Recognition, ICPR 2002 (2002)

    Google Scholar 

  6. Khashman, A., Sekeroglu, B.: Multi-banknote identification using a single neural network. In: Blanc-Talon, J., Philips, W., Popescu, D.C., Scheunders, P. (eds.) ACIVS 2005. LNCS, vol. 3708, pp. 123–129. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  7. Cambridge University, Olivetti Research Laboratory face database, http://www.uk.research.att.com/facedatabase.html

  8. Haykin, S.: Neural Networks: a Comprehensive Foundation. Prentice Hall, Upper Saddle River (1999)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical & Electronic Engineering Department, Near East University, North Cyprus

    Adnan Khashman & Akram A. Garad

Authors
  1. Adnan Khashman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akram A. Garad
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Information and Computer Science, University of California, Irvine

    Sharad Mehrotra

  2. MIS Department, University of Arizona, 85721, Tucson, AZ, USA

    Daniel D. Zeng

  3. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  4. University of Texas at Dallas,  

    Bhavani Thuraisingham

  5. Chinese Academy of Sciences, 100190, Beijing, China

    Fei-Yue Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Khashman, A., Garad, A.A. (2006). Intelligent Face Recognition Using Feature Averaging. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, FY. (eds) Intelligence and Security Informatics. ISI 2006. Lecture Notes in Computer Science, vol 3975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760146_38

Download citation

  • DOI: https://doi.org/10.1007/11760146_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34478-0

  • Online ISBN: 978-3-540-34479-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation