Abstract
The chapter presents a method that uses the cascade of neural networks for facial expression recognition. As an input the algorithm receives a normalized image of a face and returns the emotion that the face expresses. To determine the best classifiers for recognizing particular emotions one- and multilayered networks were tested. Experiments covered different resolutions of the images presenting faces as well as the images including regions of mouths and eyes. On the basis of the tests results a cascade of the neural networks was proposed. The cascade recognizes six basic emotions and neutral expression.
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References
Ekman, P.: Facial expression and emotion. American Psychologist 48(4), 384, 384–392 (1993)
Ekman, P., Friesen, W., Hager, J.: Facial action coding system. Consulting Psychologists Press, Palo Alto (1978)
Ekman, P., Hager, J., Rosenberg, E.: FACSAID: A computer database for predicting affective phenomena from facial movement (2003), http://face-and-emotion.com/dataface/facsaid/description.jsp , http://face-and-emotion.com/dataface/nsfrept/psychology.html (visited April 4, 2014)
Fasel, B., Luettin, J.: Automatic facial expression analysis: A survey. Pattern Recognition Society 36(1), 259–275 (2003)
Golomb, B.A., Lawrence, D.T., Sejnowski, T.J.: Sexnet: A neural net identifies sex from human faces. In: Lippman, R.P., Moody, J., Touretzky, D.S. (eds.) NIPS, vol. 3, pp. 572–577. Morgan Kaufmann, San Francisco (1991)
Kanade, T., Cohn, J., Tian, Y.: Comprehensive database for facial expression analysis. In: Proceedings of the Fourth IEEE International Conference on Automatic Face Gesture Recognition (FG 2000), Grenoble, France, pp. 46–53 (2000)
Lien, J., Kanade, T., Cohn, J., Li, C.: Detection, tracking and classification of action units in facial expressions. Robotics and Autonomous Systems 31(3), 131–146 (2000)
Lundqvist, D., Flykt, A., Öhman, A.: The Karolinska directed emotional faces (KDEF). CD ROM from Department of Clinical Neuroscience, Psychology section, Karolinska Institutet, pp. 91–630 (1998)
Pardàs, M., Bonafonte, A.: Facial animation parameters extraction and expression recognition using Hidden Markov Models. Signal Processing: Image Communication 17(9), 675–688 (2002)
Thiran, J.P., Marques, F., Bourlard, H. (eds.): Multimodal Signal Processing: Theory and Applications for Human-Computer Interaction. Elsevier, San Diego (2010)
Tian, Y., Kanade, T., Cohn, J.: Facial expression analysis. In: Handbook of Face Recognition, pp. 247–276 (2005)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I-511–I-518 (2001)
Yang, M.H., Kriegman, D., Ahuja, N.: Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(1), 34–58 (2002)
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Kukla, E., Nowak, P. (2015). Facial Emotion Recognition Based on Cascade of Neural Networks. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) New Research in Multimedia and Internet Systems. Advances in Intelligent Systems and Computing, vol 314. Springer, Cham. https://doi.org/10.1007/978-3-319-10383-9_7
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DOI: https://doi.org/10.1007/978-3-319-10383-9_7
Publisher Name: Springer, Cham
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