ABSTRACT
The face is an important source of information in multimodal communication. Facial expressions are generated by contractions of facial muscles, which lead to subtle changes in the area of the eyelids, eye brows, nose, lips and skin texture, often revealed by wrinkles and bulges. To measure these subtle changes, Ekman et al.[5] developed the Facial Action Coding System (FACS). FACS is a human-observer-based system designed to detect subtle changes in facial features, and describes facial expressions by action units (AUs). We present a technique to automatically recognize lower facial Action Units, independently from one another. Even though we do not explicitly take into account AU combinations, thereby making the classification process harder, an average F1 score of 94.83% is achieved.
- Bartlett, M., Littlewort, G., Lainscsek, C., Fasel, I., and Movellan, J. Machine learning methods for fully automatic recognition of facial expressions and facial actions. In IEEE International Conference on Systems, Man & Cybernetics (2004), 592--597.Google ScholarCross Ref
- Chang, C.-C. and Lin, C.-J. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm. Google ScholarDigital Library
- Clemons, T. E. and Bradley Jr., E. L. A nonparametric measure of the overlapping coefficient. Computational Statistics &. Data Analysis. 34, 1 (2000), 51--61. Google ScholarDigital Library
- Cohn, J. F., Reed, L., Moriyama, T., Xiao, J., Schmidt, K., and Ambadar, Z. Multimodal coordination of facial action, head rotation, and eye motion during spontaneous smiles. In Proc. FG2004, IEEE Computer Society (2004), 129--135. Google ScholarDigital Library
- Ekman, P., Friesen, W., and Hager, J. C. The Facial Action Coding System. Second Edition. Research Nexus eBook (2002).Google Scholar
- Hou, Y., Sahli, H., Ravyse, I., Zhang, Y., and Zhao, R. Robust Shape-Based Head Tracking. In Proc. ACIVS 2007, Springer-Verlag (2007), 340--351. Google ScholarDigital Library
- Freund, Y., and Schapire, R. E. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55, 1 (1997), 119--139. Google ScholarDigital Library
- el Kaliouby, R. Mind-Reading Machines: Automated Inference of Complex Mental States. PhD thesis, University of Cambridge, Computer Laboratory (2005).Google Scholar
- Kanade, T., Cohn, J. F., and Tian, Y. Comprehensive database for facial expression analysis. In Proc. FGR 2000, IEEE Computer Society (2000), 46--53. Google ScholarDigital Library
- Mahoor, M. H., Cadavid, S., Messinger, D. S., and Cohn, J. F. A framework for automated measurement of the intensity of non-posed facial action units. In Proc. CVPR4HB2009, 12--18.Google Scholar
- Messinger, D., Mahoor, M., Chow, S., and Cohn, J. F. Automated Measurement of Facial Expression in Infant-Mother Interaction: A Pilot Study, Infancy, 14, 3 (2009), 285--305.Google ScholarCross Ref
- Vapnik, V. N. The nature of statistical learning theory. Second Edition, Springer-Verlag (1999). Google ScholarDigital Library
- Zhang, Y. M. and Ji, Q. A. Active and dynamic information fusion for facial expression understanding from image sequences. PAMI, 27, 5 (2005), 699--714. Google ScholarDigital Library
Index Terms
- Automatic recognition of lower facial action units
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