Abstract
Facial expression recognition has been an active research topic for many years, with Facial Action Coding Systems (FACS) being among the widely used methods. FACS is a well-established scheme in psychology to annotate facial muscle contractions and relaxations, also called Action Units (AUs). Previous work on FACS-based methods focused on frontal or near-frontal head poses. In this work, we propose a method to recognize expressions in side head poses. This method builds one classifier for each possible group of occlusions. Facial expression recognition of a side facial pose is then based on a boosting approach of the different classifiers. The method is first tested with frontal and near-frontal head poses, and the results are shown to be comparable to state of the art work for AU and emotion detection. The method is then tested with a small training set for various orientations and AUs, and shown to be accurate.
This is a preview of subscription content, log in via an institution to check access.
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
Russell, J., Dols, J.: The psychology of facial expression. Studies in emotion and social interaction. Cambridge University Press (1997)
Tian, Y.L., Kanade, T., Cohn, J.F.: Facial expression recognition. In: Li, S.Z., Jain, A.K. (eds.) Handbook of Face Recognition, 2nd edn., pp. 487–519. Springer (2011)
Ekman, P., Friesen, W.V.: The facial action coding system: A technique for the of facial movement. In: Consulting Psychologists (1978)
Lien, J., Kanade, T., Cohn, J., Li, C.: Detection, tracking, and classification of action units in facial expression. Robotics and Autonomous Systems 31(3), 131–146 (2000)
Valstar, M., Pantic, M.: Fully automatic recognition of the temporal phases of facial actions. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 42(1), 28–43 (2012)
Tian, Y., Kanade, T., Cohn, J.: Recognizing action units for facial expression analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(2), 97–115 (2001)
Hu, Y., Zeng, Z., Yin, L., Wei, X., Zhou, X., Huang, T.S.: Multi-view facial expression recognition. In: FG, pp. 1–6 (2008)
Hu, Y., Zeng, Z., Yin, L., Wei, X., Tu, J., Huang, T.: A study of non-frontal-view facial expressions recognition. In: 19th International Conference on Pattern Recognition, ICPR 2008, pp. 1–4. IEEE (2008)
Tong, Y., Liao, W., Ji, Q.: Facial action unit recognition by exploiting their dynamic and semantic relationships. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(10), 1683–1699 (2007)
Pantic, M., Patras, I.: Dynamics of facial expression: Recognition of facial actions and their temporal segments from face profile image sequences. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 36(2), 433–449 (2006)
Yin, L., Wei, X., Sun, Y., Wang, J., Rosato, M.: A 3d facial expression database for facial behavior research. In: 7th International Conference on Automatic Face and Gesture Recognition, FGR 2006, pp. 211–216. IEEE (2006)
Cootes, T., Taylor, C.: Active shape models–smart snakes. In: Proc. British Machine Vision Conference, vol. 266275. Citeseer (1992)
Saragih, J., Lucey, S., Cohn, J.: Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision 91(2), 200–215 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Trad, C., Hajj, H., El-Hajj, W., Al-Jamil, F. (2012). Facial Action Unit and Emotion Recognition with Head Pose Variations. In: Zhou, S., Zhang, S., Karypis, G. (eds) Advanced Data Mining and Applications. ADMA 2012. Lecture Notes in Computer Science(), vol 7713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35527-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-35527-1_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35526-4
Online ISBN: 978-3-642-35527-1
eBook Packages: Computer ScienceComputer Science (R0)