3D Facial Expression Classification Based On Self-Organizing Mapping Network

被引：0
|
作者：
Yin, Xiaojuan [1 ]
Ju, Quan [1 ]
Li, Shuhong [1 ]
机构：
[1] Henan Univ Econ & Law, Zhengzhou, Peoples R China
来源：
2013 SEVENTH INTERNATIONAL CONFERENCE ON INTERNET COMPUTING FOR ENGINEERING AND SCIENCE (ICICSE 2013) | 2013年
关键词：
3D Facial Expression Recognition; Shape Descriptor; variance; SOM network; RECOGNITION;
D O I：
10.1109/ICICSE.2013.33
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we propose and explore a novel method to recognize human facial expression in 3D. Based on a shape descriptor to express shape in 3D converted from the original 3D points cloud, we localize the different features in 3D shape around the nose tip. Then we exploit Self-Organizing Map(SOM) to recognize the similarity of the same expression and the variations between different expresses. Experiments performed on data with facial expression variations show that our method is able to separate different expressions.
引用
收藏
页码：128 / 132
页数：5
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