ESTIMATION OF FACIAL EXPRESSION INTENSITY BASED ON THE BELIEF THEORY

Khadoudja Ghanem, Alice Caplier, Sébastien Stillittano

Abstract

This article presents a new method to estimate the intensity of a human facial expression. Supposing an expression occurring on a face has been recognized among the six universal emotions (joy, disgust, surprise, sadness, anger, fear), the estimation of the expression’s intensity is based on the determination of the degree of geometrical deformations of some facial features and on the analysis of several distances computed on skeletons of expressions. These skeletons are the result of a contour segmentation of facial permanent features (eyes, brows, mouth). The proposed method uses the belief theory for data fusion. The intensity of the recognized expression is scored on a three-point ordinal scale: "low intensity", "medium intensity" or " high intensity". Experiments on a great number of images validate our method and give good estimation for facial expression intensity. We have implemented and tested the method on the following three expressions: joy, surprise and disgust.

References

  1. Bui TD, Heylen D, Poel M, Nijholt A, 2002 « ParleE: An adaptive plan-based event appraisal model of emotions » Proceedings KI, 25th German Conference on Artificial Intelligence, eds. M Jarke, J Koehler & G Lakemeyer, Springer, Aachen, 2002.
  2. Edwards, K, 1998 The face of time: Temporal cues in facial expression of emotion. Psychological Science, 9, 270-276.
  3. I. Essa and A. Pentland, 1997 “Coding, analysis, interpretation, and recognition of facial expressions”. IEEE Trans. on Pattern Analysis and Machine Intell., 19(7):757-763.
  4. S. Kimura and M. Yachida, 1997 “Facial expression recognition and its degree estimation”. In Proc. Of the Int. Conf. on Computer Vision and Pattern Recognition, 295-300.
  5. J.J. Lien, T. Kanade, J. Cohn, and C. Li, 1998 “Subtly different facial expression recognition and expression intensity estimation”. In Proc. of the IEEE Int. Conf. on Computer Vision and Pattern Recognition, 853- 859.
  6. M. Bartlett, J. Hager, P.Ekman, and T. Sejnowski, 1999. “Measuring facial expressions by computer image analysis”. Psychophysiology, 36:253-264.
  7. Y.-L. Tian, T. Kanade, and J. Cohn, Sept 2000 “Eye-state action unit detection by Gabor wavelets”. In Proc. of Int. Conf. on Multi-modal Interfaces, 143-150.
  8. N. Eveno, A. Caplier, P.Y. Coulon. “Automatic and Accurate Lip Tracking”. IEEE Trans. on CSVT, Vol. 14, 706-715, 2004.
  9. Z. Hammal, A. Caplier. “Eye and Eyebrow Parametric Models for Automatic Segmentation”. IEEE SSIAI, Lake Tahoe, Nevada, 2004.
  10. Z. Hammal, L. Couvreur, A. Caplier, M. Rombaut “Facial Expression Classification: An approach based on the fusion of facial deformations using the Transferable Belief Model” Int. Jour. Approximate Reasonning, doi: 10.1016/j.ijar.2007.02.003, 2007.
  11. P. Ekman, W.Friesen, J. Hager, 2002 “Facial Action Coding System”. The Manual ISBN 0-931835-01-1,.
  12. A. Dempster, 1967 “Upper and lower probability inferences based on a sample from a finite univariate”. Biometrika, 54: 515-528.
  13. Shafer, Glenn, 1976. A Mathematical Theory of Evidence. Princeton University Press.
  14. P. Smets, R. Kennes, 1994 “The Transferable Belief Model”. Artificial Intelligence, 66 (2): 191-234.
  15. Hammal_Caplier Database : http://www.lis.inpg.fr/pages_perso/caplier/english/e motionnelle.html.en/emotionnelle_2.html.en.html EEBase Database : http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vimages.html
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Paper Citation


in Harvard Style

Ghanem K., Caplier A. and Stillittano S. (2008). ESTIMATION OF FACIAL EXPRESSION INTENSITY BASED ON THE BELIEF THEORY . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 452-460. DOI: 10.5220/0001076204520460


in Bibtex Style

@conference{visapp08,
author={Khadoudja Ghanem and Alice Caplier and Sébastien Stillittano},
title={ESTIMATION OF FACIAL EXPRESSION INTENSITY BASED ON THE BELIEF THEORY},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={452-460},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001076204520460},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - ESTIMATION OF FACIAL EXPRESSION INTENSITY BASED ON THE BELIEF THEORY
SN - 978-989-8111-21-0
AU - Ghanem K.
AU - Caplier A.
AU - Stillittano S.
PY - 2008
SP - 452
EP - 460
DO - 10.5220/0001076204520460