Automatic recognition of emotions from facial expressions

Henry Xue; Izidor Gertner

doi:10.1117/12.2057796

13 June 2014 Automatic recognition of emotions from facial expressions

Henry Xue, Izidor Gertner

Proceedings Volume 9090, Automatic Target Recognition XXIV; 90900O (2014) https://doi.org/10.1117/12.2057796
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

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).

Citation Download Citation

Henry Xue and Izidor Gertner "Automatic recognition of emotions from facial expressions", Proc. SPIE 9090, Automatic Target Recognition XXIV, 90900O (13 June 2014); https://doi.org/10.1117/12.2057796

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