Abstract
This paper presents a system for facial expression recognition which is designed to detect spontaneous emotions. The goal was to detect human aggression. Using a face detection algorithm, a representation of the human face was created. Then, the face texture was encoded with Gabor filter and Local Binary Pattern (LBP) operator. These techniques were used to find the feature set in emotion recognition. As a classifier, a Support Vector Machine (SVM) was applied. The system constructed was tested with spontaneous emotions for aggression detection. The numerical results indicate that the presented classifier achieved an 85% correctness recognition coefficient.
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Piątkowska, E., Martyna, J. (2012). Facial Expression Recognition for Detecting Human Aggression. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_67
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DOI: https://doi.org/10.1007/978-3-642-29347-4_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29346-7
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