Abstract
This paper addresses the problem of recognition of emotional facial gestures from static images in thumbnail resolution. More experiments are presented, a holistic and two local approaches using SVM’s as classifier engines. The experimental results related to the application of our method are reported.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bunt, H.: Issues in Multimodal Human-Computer Communication. In: Bunt, H., Beun, R.-J., Borghuis, T. (eds.) CMC 1995. LNCS (LNAI), vol. 1374, pp. 1–12. Springer, Heidelberg (1998)
Dailey, M.N., Cottrell, G.W.: PCA = Gabor for Expression Recognition. Technical Report CS-629, UCSD (1999)
Donato, G., Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J.: Classifying Facial Actions. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(10), 974–989 (1999)
Fasel, B., Luettin, J.: Automatic Facial Expression Analysis: A Survey. Pattern Recognition 36(1), 259–275 (2003)
Fazekas, A., Kotropulos, C., Buciu, I., Pitas, I.: Support vector machines on the space of Walsh functions and their properties. In: Proc. of 2nd International Symposium on Image and Signal Processing and Analysis, Pula, Croatia, June 19-21, pp. 43–48 (2001)
Fazekas, A., Sánta, I.: Recognition of Facial Gestures From Thumbnail Picture. In: Proc. of NOBIM 2004, May 27-28, Stavanger, Norway, pp. 54–57 (2004)
Fellenz, W.A., Taylor, J.G., Tsapatsoulis, N., Kolliias, S.: Comparing templatebased, feature-based and supervised classification of facial expressions from static images. In: Proceedings of Circuits, Systems, Communications and Computers (CSCC 1999), pp. 5331–5336 (1999)
Fukunaga, K.: Introduction to Statistical Pattern Recognition. Academic Press, San Diego (1990)
Joachims, T.: Making large-scale SVM learning practical. In: Advances in Kernel Methods - Support Vector Learning, pp. 169–184. MIT Press, Cambridge (1999)
Osuna, E.E., Freund, R., Girosi, F.: Support vector machines: Training and applications. CBCL Technical Report, 1–41 (March 1997)
Padgett, C., Cottrell, G.W., Adolphs, R.: Categorical perception in facial emotion classification. In: Proceedings of The Eighteenth Annual Conference of the Cognitive Science Society, San Diego, CA, pp. 249–253 (1996)
Pantic, M., Rothkrantz, L.J.M.: Automatic Analysis of Facial Expressions: The State of the Art. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12), 1424–1444 (2000)
Pantic, M., Rothkrantz, L.J.M.: Expert system for automatic analysis of facial expressions. Image and Vision Computing 18, 881–905 (2000)
Silapachote, P., Karuppiah, D.R., Hanson, A.R.: Feature selection using AdaBoost for face expression recognition. In: Proceedings of The 4th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2004, Marbella, Spain, September 2004), pp. 84–89 (2004)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1995)
Vapnik, V.N.: Statistical Learning Theory. John Wiley & Sons, New York (1998)
Vapnik, V.N.: An overview of statistical learning theory. IEEE Transactions on Neural Networks 10(5), 988–999 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fazekas, A., Sánta, I. (2005). Recognition of Facial Gestures Based on Support Vector Machines. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492429_57
Download citation
DOI: https://doi.org/10.1007/11492429_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26153-7
Online ISBN: 978-3-540-32237-5
eBook Packages: Computer ScienceComputer Science (R0)