Advertisement

Face Tracking Using the Dynamic Grey World Algorithm

  • José M. Buenaposada
  • David Sopeña
  • Luis Baumela
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2124)

Abstract

In this paper we present a colour constancy algorithm for real-time face tracking. It is based on a modification of the well known Grey World algorithm in order to use the redundant information available in an image sequence. In the experiments conducted it is clearly more robust to sudden illuminant colour changes than popular the rg-normalised algorithm.

Keywords

face tracking Grey World algorithm colour constancy 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Berwick, D., Lee., S.W.: A chromaticity space for specularity-, illumination color-and illumination pose invariant 3-d object recognition. Proc. of the Int. Conf. on Computer Vision. Bombay, India (1998)Google Scholar
  2. 2.
    Buchsbaum, G.: A spatial processor model for object colour perception. Journal of the Fanklin Institute 310 (1980) 1–26CrossRefGoogle Scholar
  3. 3.
    Bradski, G.: Computer Vision face tracking for use in a perceptual user interface. Proc. of Workshop on applications of Computer Vision, WACV’98 (1998) 214–219Google Scholar
  4. 4.
    Cheng, Y.: Mean shift, mode seeking and clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence 17 (1995) 790–799CrossRefGoogle Scholar
  5. 5.
    Crowley, J.L., Schwerdt, J.: Robust tracking and compression for video communication. Proc. of the Int. Workshop on Recognition, Analysis and Tracking of Faces and Gestures in Real-Time (RATFG’99). Corfu, Greece (1999) 2–9Google Scholar
  6. 6.
    Finlayson, G.D., Shiele, B., Crowley, J.L.: Comprehensive colour normalization. Proc. European Conf. on Computer Vison (ECCV). Vol. I. Freiburg, Germany (1998) 475–490Google Scholar
  7. 7.
    Finlayson, G.D. Shaefer, G.: Constrained dichromatic colour constancy. Proc. ECCV. Vol. II. Dublin, Ireland (2000) 342–358Google Scholar
  8. 8.
    Gershon, R., Jepson, A.D., Tsotsos, J.K.: From [R,G,B] to surface reflectance: Computing color constant descriptors in images. Proc. Int. Joint Conf. on Artificial Intelligence (1987) 755–758Google Scholar
  9. 9.
    Klinker, G.J., Shafer, S.A., Kanade, T.: A physical approach to color image understanding. International Journal of Computer Vision 4 (1990) 7–38CrossRefGoogle Scholar
  10. 10.
    Lee, H.: Method for computing the scene illuminant chromaticity from specular highlights. Journal of the Optical Society of America A 3 (1986) 1694–1699Google Scholar
  11. 11.
    Raja, Y., McKenna, S.J., Gong, S.: Colour model selection and adaptation in dynamic scenes. Proc. ECCV. Vol. I (1998) 460–474Google Scholar
  12. 12.
    Soriano, M., Martinkauppi, B., Huovinen, S., Laaksonen, M.: Skin detection in video under changing illumination conditions. Proceedings of the Int. Conference on Automatic Face and Gesture Recognition (FG’00). Grenoble, France (2000) 839–842Google Scholar
  13. 13.
    Störring, M., Andersen, H.J. Granum, E.: Estimation of the illuminant colour from human skin colour. Proceedings of the Int. Conference on Automatic Face and Gesture Recognition (FG’00). Grenoble, France (2000) 64–69Google Scholar
  14. 14.
    Toyama, K.: Prolegomena for robust face tracking. MSR-TR-98-65. Microsoft Research (Nov 1998)Google Scholar
  15. 15.
    Wu, Y., Liu, Q., Huang, T.S.: Robust real-time hand localization by self-organizing color segmentation. Proceedings RATFG’99 (1999) 161–166Google Scholar
  16. 16.
    Yang, J., Lu, W., Waibel, A.: Skin-color modeling and adaptation. Proceedings Third Asian Conference on Computer Vision, Vol. II (1998) 142–147Google Scholar
  17. 17.
    D’Zmura, M., Lennie, P.: Mechanisms of colour constancy. Journal of the Optical Society of America A 3 (1986) 1662–1672CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • José M. Buenaposada
    • 1
  • David Sopeña
    • 1
  • Luis Baumela
    • 1
  1. 1.Departamento de Inteligencia ArtificialUniversidad Politécnica de MadridMadridSpain

Personalised recommendations