Recognizing facial action units using independent component analysis and support vector machine

Document Type

Article

Publication Date

9-1-2006

Abstract

Facial expression provides a crucial behavioral measure for studies of human emotion, cognitive processes, and social interaction. In 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. © 2006.

Identifier

33744973353 (Scopus)

Publication Title

Pattern Recognition

External Full Text Location

https://doi.org/10.1016/j.patcog.2006.03.017

ISSN

00313203

First Page

1795

Last Page

1798

Issue

9

Volume

39

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