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Article type: Research Article
Authors: Teoh, Teik-Toe | Nguwi, Yok-Yen | Cho, Siu-Yeung; *
Affiliations: Centre for Computational Intelligence, School of Computer Engineering, Nanyang Technological University, Blk N4 #2A-32, Nanyang Avenue, Singapore 639798
Correspondence: [*] Corresponding author. Tel.: +65 6790 5491; Fax: +65 6792 6559; E-mail: [email protected]
Abstract: Facial expression recognition is a challenging task. A facial expression is formed by contracting or relaxing different facial muscles on human face which results in temporally deformed facial features like wide open mouth, raising eyebrows or etc. Such a system presents challenges. For instances, lighting condition is a very difficult problem to constraint and regulate. On the other hand, real-time processing is also a challenging problem since there are so many facial features to be extracted and processed and sometime conventional classifiers are not even effective to handle those features and then produce good classification performance. This paper discusses the issues on how the advanced feature selection techniques together with good classifiers can play a vital important role of real-time facial expression recognition. The content of this paper is a way to open-up a discussion about building a real-time system to read and respond to the emotions of people from facial expressions.
Keywords: Facial expression recognition, gabor feature extraction, GINI feature selection, Naïve bayesian classifier
DOI: 10.3233/IDT-2009-0062
Journal: Intelligent Decision Technologies, vol. 3, no. 3, pp. 181-191, 2009
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