13 June 2014 Automatic recognition of emotions from facial expressions
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In the human-computer interaction (HCI) process it is desirable to have an artificial intelligent (AI) system that can identify and categorize human emotions from facial expressions. Such systems can be used in security, in entertainment industries, and also to study visual perception, social interactions and disorders (e.g. schizophrenia and autism). In this work we survey and compare the performance of different feature extraction algorithms and classification schemes. We introduce a faster feature extraction method that resizes and applies a set of filters to the data images without sacrificing the accuracy. In addition, we have enhanced SVM to multiple dimensions while retaining the high accuracy rate of SVM. The algorithms were tested using the Japanese Female Facial Expression (JAFFE) Database and the Database of Faces (AT&T Faces).
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Henry Xue, Henry Xue, Izidor Gertner, Izidor Gertner, } "Automatic recognition of emotions from facial expressions", Proc. SPIE 9090, Automatic Target Recognition XXIV, 90900O (13 June 2014); doi: 10.1117/12.2057796; https://doi.org/10.1117/12.2057796


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