Facial expression recognition based on rough set theory and SVM

被引：0
|
作者：
Chen, Peijun [1 ]
Wang, Guoyin
Yang, Yong
Zhou, Jian
机构：
[1] SW Jiatong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, Chongqing 400065, Peoples R China
来源：
ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS | 2006年 / 4062卷
关键词：
facial expression recognition; rough set; support vector machines; feature extraction;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Facial expression recognition is becoming more and more important in computer application, such as health care, children education, etc. Based on geometric feature and appearance feature, there are a few works have been done on facial expression recognition using such methods as ANN, SVM, etc. In this paper, considering geometric feature only, a novel approach based on rough set theory and SVM is proposed. The experiment results show this approach can get high recognition ratio and reduce the cost of calculation.
引用
收藏
页码：772 / 777
页数：6
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