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Computer Recognition of Facial Expressions of Emotion

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Book cover Machine Learning and Data Mining in Pattern Recognition (MLDM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7376))

Abstract

In this paper, we study the computer recognition of emotions involved in facial expressions. We propose a recognition system based on a support vector machine (SVM) system as a classifier for detecting of spontaneous emotions. Using a face detection algorithm we created theface representation. Then, the face texture is encoded with Local Binary Patterns (LBP) and used as a feature set in emotion recognition. The presented classifier can be useful a.o. for aggression classification and automatic emotion exploration.

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References

  1. Ahonen, T., Hadid, A., Pietikäinen, M.: Face Recognition with Local Binary Patterns. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 469–481. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  2. Ekman, P., Friesen, W.: Facial Action Coding Systems: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto (1978)

    Google Scholar 

  3. Ekman, P., Huang, T., Sejnowski, T., Hager, J.: Final Report To NSF of the Planning Workshop on Facial Expression Understanding (1992), http://face-and-emotion.com/dataface/nsfrept/nsf_contents.html

  4. Edwards, G.J., Cootes, T.F., Taylor, C.J.: Face Recognition Using Active Appearance Models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 581–695. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  5. Essa, I., Pentland, A.: Coding, Analysis Interpretation, Recognition of Facial Expressions. IEEE Trans. Pattern Analysis and Machine Intelligence 19(7), 757–763 (1997)

    Article  Google Scholar 

  6. Hadid, A., Pietikainen, M.T., Ahonen, T.: A Discriminative Feature Space for Detecting and Recognizing Faces. In: Proc. Computer Vision and Pattern Recognition, pp. 797–804 (2004)

    Google Scholar 

  7. Huang, C.L., Huang, Y.M.: Facial Expression Recognition Using Model-Based Feature Extraction and Action Parameters Classification. J. Visual Comm. and Image Representation 8(3), 278–290 (1997)

    Article  Google Scholar 

  8. Kimura, S., Yachida, M.: Facial Expression Recognition and Its Degree Estimation. In: Proc. Computer Vision and Pattern Recognition, pp. 295–300 (1997)

    Google Scholar 

  9. Kobayashi, H., Hara, F.: Facial Interaction between Animated 3D Face Robot and Human Beings. In: Proc. Int’l Conf. Systems, Man, Cybernetics, pp. 3, 732–3, 737 (1997)

    Google Scholar 

  10. Littlewort, G.C., Bartlett, M.S., Chenu, J., Fasel, I., Kanda, T., Ishiguro, H., Movellan, J.R.: Towards Social Robots: Automatic Evaluation of Human-Robot Interaction by Face Detection and Expression Classification. In: Advances in Neural Information Processing Systems, vol. 16, pp. 1563–1570 (2004)

    Google Scholar 

  11. Ojala, T., Pietikainen, M., Harwood, D.: A Comparative Study of Texture Measures with Classification Based on Featured Distribution. Pattern Recognition 29(1), 51–59 (1996)

    Article  Google Scholar 

  12. Pantic, M., Rothkrantz, L.: Automatic Analysis of Facial Expressions: The State of the Art. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(12), 1424–1445 (2000)

    Article  Google Scholar 

  13. Pantic, M., Rothkrantz, L.: Expert System for Automatic Analysis of Facial Expression. Image and Vision Computing Journal 18(11), 881–905 (2000)

    Article  Google Scholar 

  14. Vapnik, V.N.: Statistical Learning Theory. John Wiley, New York (1998)

    MATH  Google Scholar 

  15. Viola, P., Jones, M.J.: Robust real-time object detection. International Journal of Computer Vision 57(2), 137–154 (2004)

    Article  Google Scholar 

  16. Wallhoff, F.: Facial Expressions and Emotion Database, Technische Univesität München (2006), http://www.mmk.ei.tum.de/~waf/fgnet/feedtum.html

  17. Zeng, Z., Pantic, M., Roisman, G.I., Huang, T.S.: A Survey of Affect Recognition Methods: Audio, Visual and Spontaneous Expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(1), 39–58 (2009)

    Article  Google Scholar 

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Piątkowska, E., Martyna, J. (2012). Computer Recognition of Facial Expressions of Emotion. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2012. Lecture Notes in Computer Science(), vol 7376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31537-4_32

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  • DOI: https://doi.org/10.1007/978-3-642-31537-4_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31536-7

  • Online ISBN: 978-3-642-31537-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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