Skip to main content
SpringerLink
Log in

Gravity-Center Template Based Human Face Feature Detection

  • Conference paper
  • First Online:
Advances in Multimodal Interfaces — ICMI 2000 (ICMI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1948))

Included in the following conference series:

Abstract

This paper presents a simple and fast technique for geometrical feature detection of several human face organs such as eyes and mouth. Human face gravity-center template is firstly used for face location, from which position information of face organs such as eyebrows, eyes, nose and mouth are obtained. Then the original image is processed by extracting edges and the regions around the organs are scanned on the edge image to detect out 4 key points which determine the size of the organs. From these key points, eyes and mouth’s shape are characterized by fitting curves. The results look well and the procedure is fast.

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. L.D. Harmon, The recognition of faces, Scientific American, 229(5), 71–82, 1973.

    Article  Google Scholar 

  2. G. Z. Yang and T. S. Huang, Human face detection in a complex background, Pattern Recognition, 27(1), 43–63, 1994

    Article  Google Scholar 

  3. W. Gao and M. B. Liu, A hierarchical approach to human face detection in a complex background, Proceedings of the first International Conference on Multimodal Interface’96, 289–292, 1996

    Google Scholar 

  4. A.L. Yuille, Deformable templates for face detection, J. Cogn. neurosci. 3, 59–70, 1991

    Article  Google Scholar 

  5. J. Miao, B.C. Yin, K.Q. Wang, et al, A hierarchical multiscale and multiangle system for human face detection in a complex background using gravity-center template, Pattern Recognition, 32(7), 1999

    Google Scholar 

  6. M. Turk and A. Pentland, Face recognition using eigenfaces, Proc. IEEE-CSCCVPR, 586–591, 1991

    Google Scholar 

  7. M. Kirby and L. Sirovich, Application of the Karhunen-Loeve procedure for the characterization of human faces, IEEE Trans. PAMI, 12(1), 103–108, 1990

    Google Scholar 

  8. H.A. Rowley, S. Baluja, and T. Kanade, Neural network-based face detection, IEEE-PAMI, 20(1), 23–38, 1998

    Google Scholar 

  9. K.K. Sung and T. Poggio, Example-based learning for view-based human face detection, IEEE-PAMI, 20(1), 39–50, 1998

    Google Scholar 

  10. R. Brunelli and D. Falavigna, Person identification using multiple cues, IEEE Trans. PAMI, 17(10), 955–966, 1995

    Google Scholar 

  11. C.H. Lee, J.S. Kim and K.H. Park, Automatic human face location in a complex background using motion and color information, Pattern Recognition, 29(11), 1877–1889, 1996

    Article  Google Scholar 

  12. C.J. Wu and J.S. Huang, Human faces profiles recognition by computer, Pattern Recognition, 23(3/4), 255–259, 1990

    Google Scholar 

  13. X. Li and N. Roeder, Face contour extraction from front-view images, Pattern recognition, 28(8), 1167–1179, 1995

    Article  Google Scholar 

  14. K. Lam and H. Yan, Locating and extracting the eye in human face images, Pattern recognition, 29(5), 771–779, 1996

    Article  MathSciNet  Google Scholar 

  15. A.L. Yuille, D.S. Cohen and P.W. Hallinan, Feature extraction from faces using deformable templates, Proc. IEEE-CS-CCVPR, 104–109, 1989

    Google Scholar 

  16. C.L. Huang and C.W. Chen, Human face feature extraction for face interpretation and recognition, Pattern recognition, 25(12), 1435–1444, 1996

    Article  Google Scholar 

  17. J.Y. Deng and F. Lai, Region-based template deformation and masking for eyefeature extraction and description, Pattern recognition, 30(3), 403–419, 1997

    Article  Google Scholar 

  18. S.H. Jeng, H.Y.M. Liao, et al, Facial feature detection using geometrical face model: an efficient approach, Pattern recognition, 31(3), 273–282, 1998

    Article  Google Scholar 

  19. S.Y. Lee, Y.K. Ham and R.H. Park, Recignition of human front faces using knowledge-based feature extraction and neuro-fuzzy algorithm, Pattern recognition, 29(11), 1863–1876, 1996

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Digital Media Lab, Institute of Computing Technology, Chinese Academy of Sciences, 100080, Beijing, P. R.China

    Jun Miao, Wen Gao & Yiqiang Chen

  2. Institute of Electronic Information Engineering, Tongji University, 200092, Shanghai, P. R.China

    Jie Lu

Authors
  1. Jun Miao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wen Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yiqiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jie Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, P.O.Box 2728, 100080, Beijing, China

    Tieniu Tan

  2. Computer Department, Media Laboratory, Tsinghua University, 100084, Beijing, China

    Yuanchun Shi

  3. Institute of Computing Technology, Chinese Academy of Sciences, P.O.Box 2704, 100080, Beijing, China

    Wen Gao

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Miao, J., Gao, W., Chen, Y., Lu, J. (2000). Gravity-Center Template Based Human Face Feature Detection. In: Tan, T., Shi, Y., Gao, W. (eds) Advances in Multimodal Interfaces — ICMI 2000. ICMI 2000. Lecture Notes in Computer Science, vol 1948. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40063-X_27

Download citation

  • DOI: https://doi.org/10.1007/3-540-40063-X_27

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41180-2

  • Online ISBN: 978-3-540-40063-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation