Journal
PATTERN RECOGNITION
Volume 39, Issue 9, Pages 1795-1798Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2006.03.017
Keywords
facial expression recognition; action unit; independent component analysis; support vector machine
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Facial expression provides a crucial behavioral measure for studies of human emotion, cognitive processes. and social interaction. III this paper, we focus on recognizing facial action units (AUs), which represent the subtle change of facial expressions. We adopt ICA (independent component analysis) as the feature extraction and representation method and SVM (support vector machine) as the pattern classifier. By comparing with three existing systems, such as Tian, Donato, and Bazzo, our proposed system can achieve the highest recognition rates. Furthermore, the proposed system is fast since it takes only 1.8 ms for classifying a test image. (c) 2006 Published by Elsevier Ltd on behalf of Pattern Recognition Society.
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