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Facial Expression Recognition

Facial Expression Recognition
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Author(s): Daijin Kim (Pohang University of Science & Technology, Korea)and Jaewon Sung (LG Electronics, Korea)
Copyright: 2009
Pages: 63
Source title: Automated Face Analysis: Emerging Technologies and Research
Source Author(s)/Editor(s): Daijin Kim (Pohang University of Science & Technology, Korea)and Jaewon Sung (LG Electronics, Korea)
DOI: 10.4018/978-1-60566-216-9.ch006

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Abstract

The facial expression has long been an interest for psychology, since Darwin published The expression of Emotions in Man and Animals (Darwin, C., 1899). Psychologists have studied to reveal the role and mechanism of the facial expression. One of the great discoveries of Darwin is that there exist prototypical facial expressions across multiple cultures on the earth, which provided the theoretical backgrounds for the vision researchers who tried to classify categories of the prototypical facial expressions from images. The representative 6 facial expressions are afraid, happy, sad, surprised, angry, and disgust (Mase, 1991; Yacoob and Davis, 1994). On the other hand, real facial expressions that we frequently meet in daily life consist of lots of distinct signals, which are subtly different. Further research on facial expressions required an object method to describe and measure the distinct activity of facial muscles. The facial action coding system (FACS), proposed by Hager and Ekman (1978), defines 46 distinct action units (AUs), each of which explains the activity of each distinct muscle or muscle group. The development of the objective description method also affected the vision researchers, who tried to detect the emergence of each AU (Tian et. al., 2001).

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