Skip to main content

How Face Pose Influence the Performance of SVM-Based Face and Fingerprint Authentication System

  • Conference paper
Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3644))

Included in the following conference series:

  • 4267 Accesses

Abstract

How face pose (rotating from right to left) influence the fusion authentication accuracy in face and fingerprint identity authentication system? This paper firstly tries to answer this question. The maximum rotating degree that fusion system can bear is given out by experiment. Furthermore, theoretical analysis deals with how face pose influence the fusion performance is proposed in this paper. Experiment results show that faces with big rotated degree can not be helpful but harmful to fusion system. And the maximum rotated angle of face that fusion system can bear is 20 degree. On the other hand, theoretical analysis proved that the mathematical inherence of influence of face pose on fusion system is not only the reduction of variance but also the decrease of distance between the genuine and imposter classes.

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. Hong, L., Jain, A.: Integrating Faces and Fingerprints for Personal Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(12), 1295–1307 (1998)

    Article  Google Scholar 

  2. Ben-Yacoub, S., et al.: Fusion of Face and Speech Data for Person Identity Authentication. IEEE Transactions on Neural Networks 10(5), 1065–1074 (1999)

    Article  Google Scholar 

  3. Yunhong, W., Tieniu, T.: Combining Face and Iris Biometrics for Identity Verification. In: Proceedings of the Conference on Audio- and Video-Based Biometric Person Authentication, pp. 805–813 (2003)

    Google Scholar 

  4. Ross, A., Jain, A.: Information Fusion in Biometrics. Pattern Recognition Letters 24, 2115–2125 (2003)

    Article  Google Scholar 

  5. Jain, A.K., Ross, A., et al.: An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 4–20 (2004)

    Article  Google Scholar 

  6. Hua, G., Guangda, S., et al.: Automatic Extracting the Key Points of Human Face. In: Proceeding of the 4th Conference on Biometrics Recognition, Beijing, China (2003)

    Google Scholar 

  7. Guangda, S., Cuiping, Z., et al.: MMP-PCA Face Recognition Method. Electronics Letters 38(25), 1654–1656 (2002)

    Article  Google Scholar 

  8. Ruke, H.: Research on the Multi-Hierarchical Algorithm for Fast Fingerprint Recognition. Bachelor thesis of Tsinghua University (2002)

    Google Scholar 

  9. Theodoridis, S.: Konstantinos Koutroumbas: Pattern Recognition. Elsevier Science, Amsterdam (2003)

    Google Scholar 

  10. Chunhong, J., Guangda, S.: Information Fusion in Face and Fingerprint Identity Authentication System. In: Proceeding of ICMLC 2004, vol. 1-7, pp. 3529–3535 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jiang, C., Su, G. (2005). How Face Pose Influence the Performance of SVM-Based Face and Fingerprint Authentication System. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_33

Download citation

  • DOI: https://doi.org/10.1007/11538059_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28226-6

  • Online ISBN: 978-3-540-31902-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics