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Proceedings Paper

Automatic recognition of emotions from facial expressions
Author(s): Henry Xue; Izidor Gertner
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Paper 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).

Paper Details

Date Published: 13 June 2014
PDF: 12 pages
Proc. SPIE 9090, Automatic Target Recognition XXIV, 90900O (13 June 2014); doi: 10.1117/12.2057796
Show Author Affiliations
Henry Xue, The City College of New York (United States)
Izidor Gertner, The City College of New York (United States)

Published in SPIE Proceedings Vol. 9090:
Automatic Target Recognition XXIV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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