Skip to main content

Face detection by direct convexity estimation

  • Facial Features Localisation
  • Conference paper
  • First Online:
Audio- and Video-based Biometric Person Authentication (AVBPA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1206))

  • 2410 Accesses

Abstract

We suggest a novel attentional mechanism for detection of smooth convex and concave objects based on direct processing of intensity values. The operator detects the regions of the eyes and hair in a facial image, and thus allows us to infer the face location and scale. Our operator is robust to variations in illumination, scale, and face orientation. Invariance to a large family of functions, serving for lighting improvement in images, is proved. An extensive comparison with edgebased methods is delineated.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. M.C. Burl, T.K. Leung, P. Perona. Face Localization via Shape Statistics, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  2. Y. Dai, Y. Nakano. Extraction of Facial Images from Complex Background Using Color-Information and SGLD Matrices, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  3. H.P. Graf, T. Chen, E. Petajan, E. Cosatto. Locating Faces and Facial Parts, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  4. A. Jacquin, A. Eleftheriadis. Automatic Location Tracking of Faces and Facial Features in Video Sequences, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  5. B. Moghaddam, A. Pentland. Maximum Likelihood Detection of Face and Hands, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  6. D. Reisfeld, H. Wolfson, Y. Yeshurun. Context Free Operators: The Generalized Symmetry Transform, Intl. Journal of Computer Vision, Vol. 14, 1995.

    Google Scholar 

  7. H.A. Rowley, S. Baluja, T. Kanade. Human Face Detection in Visual Scenes, will appear in: Advances in Neural Information Processing Systems 8.

    Google Scholar 

  8. B. Schiele, A. Waibel. Gaze Tracking Based on Face-Color, Proc. of the Intl. Workshop on Auto. Face-and Gesture-Recognition, Zurich, 1995.

    Google Scholar 

  9. K-K. Sung, T. Poggio. Example-Based Learning for View-Based Human Face Detection, in Proc. from Image Understanding Workshop, Monterey, CA, Nov. 1994.

    Google Scholar 

  10. S.W. Zucker, M.S. Langer, L.A. Iverson, P. Breton. Shading Flows and Scenel Bundles: A New Approach to Shape from Shading, ECCV '92, Springer-Verlag.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Josef Bigün Gérard Chollet Gunilla Borgefors

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tankus, A., Yeshurun, H., Intrator, N. (1997). Face detection by direct convexity estimation. In: Bigün, J., Chollet, G., Borgefors, G. (eds) Audio- and Video-based Biometric Person Authentication. AVBPA 1997. Lecture Notes in Computer Science, vol 1206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015978

Download citation

  • DOI: https://doi.org/10.1007/BFb0015978

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62660-2

  • Online ISBN: 978-3-540-68425-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics