In this paper, we propose a method for pose-invariant facial expression recognition from monocular video sequences. The advantage of our method is that, unlike existing methods, our method uses a very simple model, called the variable-intensity template, for describing different facial expressions, making it possible to prepare a model for each person with very little time and effort. Variable-intensity templates describe how the intensity of multiple points defined in the vicinity of facial parts varies for different facial expressions. By using this model in the framework of a particle filter, our method is capable of estimating facial poses and expressions simultaneously. Experiments demonstrate the effectiveness of our method. A recognition rate of over 90% was achieved for horizontal facial orientations on a range of ±40 degrees from the frontal view. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kumano, S., Otsuka, K., Yamato, J., Maeda, E., & Sato, Y. (2007). Pose-invariant facial expression recognition using variable-intensity templates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4843 LNCS, pp. 324–334). Springer Verlag. https://doi.org/10.1007/978-3-540-76386-4_30
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