Geometrical Approaches for Facial Expression Recognition using Support Vector Machines

被引：0
|
作者：
Fernandes Junior, Jovan de Andrade [1 ]
Matos, Leonardo Nogueira [1 ]
dos Santos Aragao, Maria Gessica [1 ]
机构：
[1] Univ Fed Sergipe, Comp Sci Dept, DCOMP, Sergipe, Brazil
来源：
2016 29TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI) | 2016年
关键词：
Facial Expression Recognition; PDM; CFS; Correlation Features Selection; Cohn-Kanade Database;
D O I：
10.1109/SIBGRAPI.2016.52
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article presents two facial geometric-based approaches for facial expression recognition using support vector machines. The first method performed an experimental research to identify the relevant geometric features for human point of view and achieved 85% of recognition rate. The second experiment employed the Correlation Feature Selection and achieved 96.11% of recognition rate. All experiments were carried out with Cohn-Kanade database and the results obtained are compatible with the state-of-the-art in this in this research area.
引用
收藏
页码：347 / 354
页数：8
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