ON-LINE FACE TRACKING UNDER LARGE LIGHTING CONDITION VARIATIONS USING INCREMENTAL LEARNING

Lyes Hamoudi, Khaled Boukharouba, Jacques Boonaert, Stéphane Lecoeuche

Abstract

To be efficient outdoors, automated video surveillance systems should recognize and monitor humans activities under various amounts of light. In this paper, we present a human face tracking system that is based on the classification of the skin pixels using colour and texture properties. The originality of this work concerns the use of a specific dynamical classifier. An incremental svm algorithm equipped with dynamic learning and unlearning rules, is designed to track the variation of the skin-pixels distribution. This adaptive skin classification system is able to detect and track a face in large lighting condition variations.

References

  1. Cauwenberghs, G. and Poggio, T. (2000). Incremental and decremental support vector machine learning. In Neural Information Processing Systems.
  2. Chai, D. and Ngan, K. (1998). Locating facial region of a head-and-shoulders colour image. In 3rd IEEE International Conference on Automatic Face and Gesture Recognition.
  3. Chow, T., Lam, K., and Wong, K. (2006). Efficient colour face detection algorithm under different lighting conditions. Journal of Electronic Imaging, 15(1):013015.
  4. Cula, O., Dana, K., Murphy, F., and Rao, B. (2005). Skin texture modeling. International Journal of Computer Vision, 62 (1-2):97-119.
  5. Forsyth, D. and Fleck, M. (1999). Automatic detection of human nudes. International Journal of Computer Vision, 32(1):63-77.
  6. La Cascia, M., Sclaroff, M., and Athitso, S. (2000). Fast reliable head tracking under varying illumination: An ap-proach based on robust registration of texture mapped 3d models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(4):332-336.
  7. Martinkauppi, B. (2002). Face Colour Under Varying Illumination -Analysis And Applications. PhD thesis, Department of Electrical and Information Engineering and Infotech Oulu, University of Oulu.
  8. McKenna, S., Raja, Y., and Gong, S. (1999). Tracking colour objects using adaptive mixture models. Image and Vision Computing, 17(3-4):225-231.
  9. Sigal, L., Sclaroff, S., and Athitsos, V. (2004). Skin colourbased video segmentation under time-varying illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(7):862-877.
  10. Soriano, M., Martinkauppi, B., Huovinen, S., and Laaksonen, M. (2000). Using the skin locus to cope with changing illumination conditions in colour-based face tracking. In IEEE Nordic Signal Processing Symposium.
  11. Strring, M., Andersen, H. J., and Granum, E. (1999). Skin colour detection under changing lighting conditions. In 7th International Symposium on Intelligent Robotic Systems.
  12. Vapnik, V. (1995). The Nature of Statistical Learning Theory.
  13. Yang, M., Kriegman, D., and Ahuja, N. (2002). Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1):34-58.
Download


Paper Citation


in Harvard Style

Hamoudi L., Boukharouba K., Boonaert J. and Lecoeuche S. (2009). ON-LINE FACE TRACKING UNDER LARGE LIGHTING CONDITION VARIATIONS USING INCREMENTAL LEARNING . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 636-643. DOI: 10.5220/0001806106360643


in Bibtex Style

@conference{visapp09,
author={Lyes Hamoudi and Khaled Boukharouba and Jacques Boonaert and Stéphane Lecoeuche},
title={ON-LINE FACE TRACKING UNDER LARGE LIGHTING CONDITION VARIATIONS USING INCREMENTAL LEARNING},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={636-643},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001806106360643},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)
TI - ON-LINE FACE TRACKING UNDER LARGE LIGHTING CONDITION VARIATIONS USING INCREMENTAL LEARNING
SN - 978-989-8111-69-2
AU - Hamoudi L.
AU - Boukharouba K.
AU - Boonaert J.
AU - Lecoeuche S.
PY - 2009
SP - 636
EP - 643
DO - 10.5220/0001806106360643