Facial expression recognition based on dimension model using sparse coding

被引:0
作者
Shin, YS [1 ]
机构
[1] Chosun Univ, Dept Informat & Telecommun Engn, Kwangju 501759, South Korea
来源
COMPUTATIONAL SCIENCE - ICCS 2004, PROCEEDINGS | 2004年 / 3039卷
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present an expression recognition system based on dimension model of internal states that is capable of identifying the various emotions using automated feature extraction. Feature vectors for facial expressions are extracted from a hybrid approach using fuzzy c-mean clustering algorithm and dynamic linking based on Gabor wavelet representation. The result of facial expression recognition is compared with dimensional values of internal states derived from semantic ratings of words related to emotion by experimental subjects. The dimensional model recognizes not only six facial expressions related to six basic emotions (happiness, sadness, surprise, angry, fear, disgust), but also expressions of various internal states. In this paper, with dimension model we have improved the limitation of expression recognition based on basic emotions, and have extracted features automatically with a new approach using FCM algorithm and the dynamic linking model.
引用
收藏
页码:205 / 212
页数:8
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