S. Canu, Svm and kernel machines : linear and non-linear classification. Ocean's Big Data Mining, 2014.

C. Chan, J. Kittler, and E. K. Messer, Multi-scale Local Binary Pattern Histograms for Face Recognition, International Conference on Biometrics, pp.809-818, 2007.
DOI : 10.1007/978-3-540-74549-5_85

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995.
DOI : 10.1007/BF00994018

E. Frank, M. Et, and . Hall, A Simple Approach to Ordinal Classification, European Conference on Machine Learning, pp.145-156, 2001.
DOI : 10.1007/3-540-44795-4_13

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

A. J. Gerber, J. Posner, D. Gorman, T. Colibazzi, S. Yu et al., An affective circumplex model of neural systems subserving valence, arousal, and cognitive overlay during the appraisal of emotional faces, Neuropsychologia, vol.46, issue.8, pp.2129-2139, 2008.
DOI : 10.1016/j.neuropsychologia.2008.02.032

Y. Guermeur and H. Paugam-moisy, Théorie de l'apprentissage de Vapnik et SVM, pp.109-138, 1999.

M. Kächele, M. Schels, and E. F. Schwenker, Inferring Depression and Affect from Application Dependent Meta Knowledge, Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge, AVEC '14, pp.41-48, 2014.
DOI : 10.1145/2661806.2661813

J. Milgram, M. Cheriet, and E. R. Sabourin, one against one" or "one against all" : Which one is better for handwriting recognition with svms ?, Tenth International Workshop on Frontiers in Handwriting Recognition, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00103955

R. W. Picard, Affective computing, 1997.
DOI : 10.1037/e526112012-054

L. Prevost, P. Phothisane, and E. E. Bigorgne, Live stream oriented age and gender estimation using boosted lbp histograms comparisons, Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, pp.790-798, 2014.

G. A. Ramirez, T. Baltru?aitis, and L. Morency, Modeling Latent Discriminative Dynamic of Multi-dimensional Affective Signals, Affective Computing and Intelligent Interaction, pp.396-406, 2011.
DOI : 10.1007/978-3-642-24571-8_51

J. Russell, A circumplex model of affect., Journal of Personality and Social Psychology, vol.39, issue.6, pp.1161-1178, 1980.
DOI : 10.1037/h0077714

URL : https://hal.archives-ouvertes.fr/hal-01086372

B. Schuller, M. Valstar, F. Eyben, G. Mckeown, R. Cowie et al., AVEC 2011???The First International Audio/Visual Emotion Challenge, International Conference on Affective Computing and Intelligent Interaction, pp.415-424, 2011.
DOI : 10.1007/978-3-642-24571-8_53

T. Senechal, K. Bailly, and E. L. Prevost, Automatic Facial Action Detection Using Histogram Variation Between Emotional States, 2010 20th International Conference on Pattern Recognition, pp.3752-3755, 2010.
DOI : 10.1109/ICPR.2010.914

M. Valstar, B. Schuller, K. Smith, F. Almaev, J. Eyben et al., AVEC 2014, Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge, AVEC '14, pp.3-10, 2014.
DOI : 10.1145/2661806.2661807

P. Viola, M. Et, and . Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, p.511, 2001.
DOI : 10.1109/CVPR.2001.990517

J. R. Williamson, T. F. Quatieri, B. S. Helfer, G. Ciccarelli, and D. D. Mehta, Vocal and Facial Biomarkers of Depression based on Motor Incoordination and Timing, Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge, AVEC '14, pp.65-72, 2014.
DOI : 10.1145/2661806.2661809