Skip to main content
SpringerLink
Log in

Innertron: New Methodology of Facial Recognition, Part I

  • Conference paper
Intelligent Information Processing and Web Mining

Part of the book series: Advances in Soft Computing ((AINSC,volume 31))

Abstract

On October 10, 2001, the US President identified the most wanted persons sought by the United States of America. Agencies such as FBI, CIA and Homeland Security spread images of the most wanted persons across the United States. Even though US citizens saw their images on television, the Internet and posters, computers had, and still have for that matter, no ability at all to identify these persons. To date FBI, CIA and Homeland Security depend entirely on human beings, not computers, to identify persons at borders and international airports. In other words, facial recognition remains an incompetent technology.

Accordingly, authors first succinctly show the weaknesses of the current facial recognition methodologies, namely Eigenface Technology, Local Feature Analysis (from the classical 7 point to the 32–50 blocks approach), the Scale-Space Approach, Morphological Operations and industrial or patented methodologies such as ILEFIS™, Viisage™, Visionics™ and Cognitec’s FaceVACS-Logon™, Identix™ and Neven Vision™. Secondly, they introduce a completely new, simple and robust methodology called Innertron.

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 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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. Patsuris, P. (2004), Homeland Security: Viisage Puts On A Good Face, 04.22.04, 8:00 AM ET, See: http://www.forbes.com/technology/2004/04/22/cx_pp_0421visage_ii.html

    Google Scholar 

  2. OMIT, http://www.forbes.com/technology/2004/04/22/cx_pp_0421visage_ii.html

    Google Scholar 

  3. See: http://www.frost.com/prod/servlet/search-results.pag?srchid=28266978

    Google Scholar 

  4. Morrison, P. (2002), More Than a Face in the Crowd, WPI Transofmations, See: http://www.wpi.edu/News/Transformations/2002Spring/face.html

    Google Scholar 

  5. Bray, H. (2002), The Boston Globe, Jul 17, See: http://www.boston.com/dailyglobe2/198/metro/_Face_testing_at_Logan_is_found_lacking+.shtml

    Google Scholar 

  6. Willing, R. (2003), Airport anti-terror systems flub tests, USA TODAY, Posted 9/1/2003, 11:14 PM, Updated 9/2/2003, 7:53 AM, See: http://www.usatoday.com/news/nation/2003-09-01-faces-usat_x.htm

    Google Scholar 

  7. See: http://www.identix.com/products/pro_security_bnp_argus.html

    Google Scholar 

  8. Stanley, J., Steinhardt, B. (2002), Drawing a Blank: The failure of facial recognition technology, in Tampa, Florida, AN ACLU SPECIAL REPORT, Jan 3

    Google Scholar 

  9. Black, J. (2001), Face It, Face-Cams Are Here to Stay, BusinessWeek Online, NOVEMBER 15, 2001. See: http://www.businessweek.com/bwdaily/dnflash/nov2001/nf20011115_3919.htm

    Google Scholar 

  10. Feder B. (2004), Technology Strains to Find Menace in the Crowd; Face-Recognition Technology Comes of Age. The New York Times, 06/04/2004, See: http://www.policeone.com/police-technology/software/facial/articles/88418/

    Google Scholar 

  11. Thalheim, L., Krissler, J., Ziegler, P. (2002), Body Check: Biometric Access Protection Devices and their Programs, Put to the Testc’t 11/2002, page 114 Biometrie, See: http://www.heise.de/ct/english/02/11/114/

    Google Scholar 

  12. Leyden, J. (2002), The Register, Security-Biometric sensors beaten senseless in tests, published Thursday, 23rd May, 2002, 05:44 GMT. See: http://www.theregister.com/2002/05/23/biometric_sensors_beaten_senseless/

    Google Scholar 

  13. Neven, H. (2004), Neven Vision Machine Technology, See: http://www.nevenvision.com/co_neven.html

    Google Scholar 

  14. Pasquerello, M. (2004), Neven Vision and Graphco Blend Face and Voice Recognition to Secure Military, Government and Transportation Facilities, in BiometritchNews, May 12, 2004, See: http://www.tmcnet.com/usubmit/2004/May/1041332.htm

    Google Scholar 

  15. Okada, K. (2001), Analysis, Synthesis and Recognition of Human Faces with Pose Variations, Ph.D. Thesis, Univ. of Southern California, Computer Science

    Google Scholar 

  16. Graham, D., Allinson, N. (1998), Characterizing virtual eigensignatures for general purpose face recognition, in Face Recognition: From Theory to Applications, Springer-Verlag, 446–456

    Google Scholar 

  17. Graham, D., Allinson, N. (1998), Face recognition from unfamiliar views: Subspace methods and pose dependency, in Proceedings of Third International Conference on Automatic Face and Gesture Recognition, 348–353

    Google Scholar 

  18. Wieghardt, J., von der Malsburg, C. (2000), Pose-independent object representation by 2-D views, in Proceedings of IEEE International Workshop on Biologically Motivated Computer Vision, May

    Google Scholar 

  19. Turk M. and Pentland, A. (1991), Face recognition using eigenfaces, in Proc. IEEE Conference on Computer Vision and Pattern Recognition, Maui, Hawaii

    Google Scholar 

  20. Turk M. and Pentland, A. (1991), Eigenfaces for recognition, in Journal of Cognitive Neuroscience, Vol. 3, No. 1, 71–86

    Google Scholar 

  21. See: http://www.cs.ucsb.edu/etc/news/past/2000.shtml

    Google Scholar 

  22. Marcus., Minc. 1988 Page 144.

    Google Scholar 

  23. Pentland A., Moghaddam, B., Starner, T., Oliyide, O., Turk, M. (1993), View-Based and Modular Eigenspaces for Face Recognition, Technical Report 245, MIT Media Lab.

    Google Scholar 

  24. Pentland L., Kirby, M. (1987), Low-dimensional procedure for the characterization of human faces, Journal of the Optical Society of America, No. 4, 519–524

    Article  Google Scholar 

  25. Kirby, M., Sirovich, L. (1990), Application of the Karhunen-Loeve procedure for the characterization of human faces, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 1, 103–108

    Article  Google Scholar 

  26. Turk M. and Pentland, A. (1991), Eigenfaces for Recognition, Journal of Cognitive Neuroscience, Vol. 3, No. 1

    Google Scholar 

  27. Rowley A., Baluja, S., Kanade, T. (1997), Rotation invariant neural network-based face detection, CS Technical Report, CMU-CS-97-201, CMU, Pittsburgh

    Google Scholar 

  28. Schneiderman H., Kanade, T. (1998), Probabilistic modeling of local appearance and spatial relationships for object recognition, in Proc. IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, 4551

    Google Scholar 

  29. John Moran Eye Center University of Utah, See: http://webvision.med.utah.edu/imageswv/scan.jpeg

    Google Scholar 

  30. See: http://before.eyelids-blepharoplasty.com/sub_anatomy.html

    Google Scholar 

  31. See: http://www.drmeronk.com/blephnews/anatomy.html#external

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Dept., UNC-Charlotte, Charlotte, NC, 28223, USA

    Rory A. Lewis & Zbigniew W. Raś

  2. Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237, Warsaw, Poland

    Zbigniew W. Raś

Authors
  1. Rory A. Lewis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zbigniew W. Raś
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computer Sciences, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warszawa, Poland

    Mieczysław A. Kłopotek , Sławomir T. Wierzchoń  & Krzysztof Trojanowski ,  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lewis, R.A., Raś, Z.W. (2005). Innertron: New Methodology of Facial Recognition, Part I. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_74

Download citation

  • DOI: https://doi.org/10.1007/3-540-32392-9_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25056-2

  • Online ISBN: 978-3-540-32392-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation