Skip to main content

A Face Detection Using Multiple Detectors for External Environment

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

Included in the following conference series:

  • 1616 Accesses

Abstract

We propose a method of multiple context fusion based robust face detection scheme, multiple cascade and finally decision using correlation table. It takes advantage of multiple cascade face detector fusion by context. We propose the filtering classifier method for illumination face image. And then we constructed cascade classifier from applied different filtering method. The multiple cascade detectors made from six single context detectors. Six contexts are divided k-means algorithm, and classify illuminant. In this paper, we proposed the classifier fusion method by using correlation between face images. The proposed face detection achieves the capacity of the high level attentive process by taking advantage of the context-awareness using the information from illumination. We achieved very encouraging experimental results having varying illuminant.

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. Kuncheva, L.I.: Switching Between Selection and Fusion in Combining Classifiers: An Experiment. IEEE Transactions on Systems, Man, and Cybernetics - part B: cybernetics 32(2), 146–156 (2002)

    Article  Google Scholar 

  2. Kuncheva, L.I.: A Theoretical Study on Six Classifier Fusion Strategies. IEEE S on PAMI 24(2) (2002)

    Google Scholar 

  3. Kuncheva, L.I., Bezdek, J.C., Duin, R.P.W.: Decision templates for multiple classifier fusion: An experimental comparison. Pattern Recognit. 34(2), 299–314 (2001)

    Article  MATH  Google Scholar 

  4. Huang, Y.S., Suen, C.Y.: A Method of Combining Multiple Classifiers—A Neural Network Approach. In: Proc. 12th Int’l Conf. Pattern Recognition

    Google Scholar 

  5. Yau, S., Karim, F., Wang, Y., Wang, B., Gupta, S.: Reconfigurable Context-Sensitive Middleware for Pervasive Computing. IEEE Pervasive Computing 1(3), 33–40 (2002)

    Article  Google Scholar 

  6. Nam, M.Y., Rhee, P.K.: An Efficient Face Recognition for Variant Illumination Condition. In: ISPACS 2005, vol. 1, pp. 111–115 (2004)

    Google Scholar 

  7. Nam, M.Y., Rhee, P.K.: A Novel Image Preprocessing by Evolvable Neural Network, LNAI 3214, Vol.3, pp.843-854 (2004)

    Google Scholar 

  8. Kuncheva, L.I., Jain, L.C.: Designing classifier fusion systems by genetic algorithms. IEEE Transactions on Evolutionary Computation 4(4), 327–336 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nam, M.Y., Kyu, P. (2006). A Face Detection Using Multiple Detectors for External Environment. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_161

Download citation

  • DOI: https://doi.org/10.1007/11881599_161

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics