Abstract
The study presents results of analysis of spontaneous facial expression. Their purpose was to isolate aggression from the facial expressions. Based on tracking specific points of a face, selected from a video sequence, a trajectory of the face’s movement was made. Then, using the Gabor filter and Local Binary Patterns (LBP) operator, extraction and analysis of the facial features was performed, from which vectors of aggression features have been detailed. Using the support vector machine (SVM) classifier, classification of the spontaneous facial data was made in order to detect the aggression. A correct recognition rate of the method, as high as 85% as well as a high ability for generalization was obtained.
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Piątkowska, E., Martyna, J. (2012). Spontaneous Facial Expression Recognition: Automatic Aggression Detection. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_14
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DOI: https://doi.org/10.1007/978-3-642-28942-2_14
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