Abstract
This paper treats methodology to build linked data from the relationships between facial action units and their states as emotional parameters for the facial emotion recognition. In this paper, the authors are especially focusing on building action unit-based linked data because it will be possible not only to use the data for the facial emotion recognition but also to enhance the usefulness of the data by merging them with other linked data. Although in general, the representation as linked data seems to make the accuracy of the facial emotion recognition lower than others, in practically the proposed method that uses action unit-based linked data has almost the same accuracy for the facial emotion recognition as those of other approaches like using Artificial Neural Network and using Support Vector Machine.
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Kaneko, K., Okada, Y. (2013). Action Unit-Based Linked Data for Facial Emotion Recognition. In: Yoshida, T., Kou, G., Skowron, A., Cao, J., Hacid, H., Zhong, N. (eds) Active Media Technology. AMT 2013. Lecture Notes in Computer Science, vol 8210. Springer, Cham. https://doi.org/10.1007/978-3-319-02750-0_22
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DOI: https://doi.org/10.1007/978-3-319-02750-0_22
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