PHOTOGENIC FACIAL EXPRESSION DISCRIMINATION

Luana Bezerra Batista, Herman Martins Gomes, João Marques de Carvalho

Abstract

Facial Expression Recognition Systems (FERS) are usually applied to human-machine interfaces, enabling services that require identification of the emotional state of the user. This paper presents a new approach to the facial expression recognition problem, by addressing the question of whether or not it is possible to classify previously labeled photogenic and non-photogenic face images, based on their appearance. A Multi-Layer Perceptron (MLP) is trained with PCA representations of the face images to learn the relationships between facial expressions and the concept of a good photography of the face of a person. In the experiments, the generalization performances using MLP and Support Vector Machines (SVM) were analyzed. The results have shown that Principal Component Analysis (PCA) combined with MLP represent a promising approach to the problem.

References

  1. Bartlett, M., Littlewort, G., Braathen, B., Sejnowski, T. and Movellan, J., 2002. An Approach to Automatic Analysis of Spontaneous Facial Expressions. Neural Information Processing Systems.
  2. Borod, J, Koff, E., Yecker, S., Santschi-Haywood, C. and Schmidt, J., 1998. Facial asymmetry during emotional expression: Gender, valence, and measurement technique. Neuropsychologia, vol. 36, no. 11, pp. 1209-1215.
  3. Chang, C. and Lin, J. LIBSVM v2.8: a library for support vector machines, 2005. Available at online http://www.csie.ntu.edu.tw/cjlin/libsvm.
  4. Chibelushi, C. and Bourel, F., 2003. Facial Expression Recognition: A Brief Tutorial Overview. In On-Line Compendium of Computer Vision.
  5. van Dam, A., 2000. Beyond WIMP. In IEEE Computer Graphics and Applications, vol. 20, no. 1, pp. 50-51.
  6. Donato, G, Bartlett, M., Hager, J., Ekman, P. and Sejnowski, T., 1999. Classifying Facial Actions. In IEEE Trans.Pattern Analysis and Machine Intelligence. vol. 21, no. 10, pp. 974-989.
  7. Ekman, P., 1982. Emotion in the Human Face, Cambridge University Press.
  8. Feitosa, R., Vellasco, M., Oliveira, D., Andrade, D. and Maffra, S., 2000. Facial Expression Classification using RBF and Back-Propagation Neural Networks. In 4th World Multiconference on Systemics, Cybernetics and Informatics and the 6th International Conference on Information Systems Analysis and Synthesis, pp. 73-77.
  9. Foresee, F. and Hagan, M., 1997. Gauss-Newton approximation to Bayesian regularization. In International Joint Conference on Neural Networks, pp. 1930-1935.
  10. Haykin, S., 1998. Neural Networks: A Comprehensive Foundation, 2nd Edition, Prentice Hall.
  11. Hjelmas, E. and Low, B., 2001. Face Detection: A Survey. In Image and Vision Understanding, vol.83, pp. 236-274.
  12. Hornik, K., Stinchcombe, M. and White, H., 1989. Multilayer Feedforward Networks are Universal Approximators. In Neural Networks, vol. 2, pp. 359- 366.
  13. Kanade, T., Cohn, J. and Tian, Y., 2000. Comprehensive Database for Facial Expression Analysis. In 4th IEEE International Conference on Automatic Face and Gesture Recognition, pp. 46-53.
  14. Kapoor, A., Qi, Y. and Picard, R, 2003. Fully Automatic Upper Facial Action Recognition. In IEEE International Workshop on Analysis and Modeling of Faces and Gestures.
  15. Lee, T., 1996. Image representation using 2d Gabor wavelets. IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 959-971.
  16. Lyons, M, Akamatsu, S., Kamachi, M. and Gyoba, J., 1998. Coding Facial Expressions with Gabor Wavelets. IEEE International Conference on Automatic Face and Gesture Recognition.
  17. Matsugu, M, Mori, K., Mitarai, Y. and Kaneda, Y., 2003. Facial expression recognition combined with robust face detection in a convolutional neural network. International Joint Conference on Neural Networks, vol. 3, pp. 2243 - 2246.
  18. Mehrabian, A., 1968. Communication without Words. In Psychology Today, vol. 2, no. 4, pp 53-56.
  19. Nakano, M., Mitsukura, Y., Fukumi, M. and Akamatsu, N., 2002. True Smile Recognition System using Neural Networks. In International Conference on Neural Information, pp. 1-5.
  20. Pantic, M. and Rothkrantz, L., 2000. Automatic Analysis of Facial Expressions: The State of the Art. In IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 12, pp.1424-1445.
  21. Pentland, A., 2000. Looking at People: Sensing for Ubiquitous and Wearable Computing. In IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 107-119.
  22. Shinohara, Y. and Otsu, N., 2004. Facial Expression Recognition Using Fisher Weight Maps”, International Conference on Automatic Face and Gesture Recognition, pp. 499-504.
  23. Vapnik, V., 1999. The Nature of Statistical Learning Theory, 2nd Edition, Springer-Verlag, New York.
  24. Zhang, Z., Lyons, M., Schuster, M. and Akamatsu, S., 1998. Comparison between geometry-based and Gabor wavelets based facial expression recognition using multi-layer perceptron”. IEEE International Conference on Automatic Face and Gesture Recognition.
  25. Zue, V. and Glass, J., 2000. Conversational Interfaces: Advances and Challenges. In IEEE, vol. 88, no. 8, pp. 1166-1180.
Download


Paper Citation


in Harvard Style

Bezerra Batista L., Martins Gomes H. and Marques de Carvalho J. (2006). PHOTOGENIC FACIAL EXPRESSION DISCRIMINATION . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 166-171. DOI: 10.5220/0001370901660171


in Bibtex Style

@conference{visapp06,
author={Luana Bezerra Batista and Herman Martins Gomes and João Marques de Carvalho},
title={PHOTOGENIC FACIAL EXPRESSION DISCRIMINATION},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={166-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001370901660171},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - PHOTOGENIC FACIAL EXPRESSION DISCRIMINATION
SN - 972-8865-40-6
AU - Bezerra Batista L.
AU - Martins Gomes H.
AU - Marques de Carvalho J.
PY - 2006
SP - 166
EP - 171
DO - 10.5220/0001370901660171