Expression Recognition Based on Genetic Algorithm and SVM

被引：0
|
作者：
Zhu, Ya-ni [1 ]
Du, Jia-you [1 ]
Song, Jia-tao [2 ]
机构：
[1] Hangzhou Dianzi Univ, Dept Sci & Technol, Hangzhou 310018, Peoples R China
[2] Ningbo Univ Technol, Coll Electron & Informat Engn, Ningbo, Peoples R China
来源：
FUZZY INFORMATION AND ENGINEERING, VOLUME 2 | 2009年 / 62卷
关键词：
Expression recognition; equable principal component analysis; support vector machine; genetic algorithm;
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：
In this paper, a novel expression recognition scheme is presented. Our method uses Equable Principal Component Analysis (EPCA) as expression features representation and employs Support Vector Machine (SVM) based on Genetic Algorithm(GA) as expression classifier. EPCA can reduce the dimensions of feature vectors; and GA can select excellent SVM kernel function. Experiments of human are performed on the JAFFE and Yale database, and compared to the nearest classifier, our method can get better recognition ratio.
引用
收藏
页码：743 / +
页数：2
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