Facial expression recognition based on two-stage features extraction

被引:24
作者
Lai, Chih-Chin [1 ]
Ko, Chung-Hung [1 ]
机构
[1] Natl Univ Kaohsiung, Dept Elect Engn, Kaohsiung 81148, Taiwan
来源
OPTIK | 2014年 / 125卷 / 22期
关键词
Facial expression recognition; Threshold local binary pattern; Center-symmetric local binary pattern; Support vector machine; LOCAL BINARY PATTERNS;
D O I
10.1016/j.ijleo.2014.08.052
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Facial expression recognition plays an important role in a variety of real-world applications such as human-computer interaction, robot control, smart meeting, and visual surveillance. One critical step for facial expression recognition is to accurately extract emotional features. In this article, a facial expression recognition approach based on two-stage local facial textures extraction is proposed. At the first stage, we use the threshold local binary pattern to transform a facial image into a feature image. We then extract the most discriminate features from the feature image by using the block-based center-symmetric local binary pattern. Finally, these features are classified by the support vector machine. Experimental results are provided to illustrate the proposed approach is an effective method, compared to other similar methods. (C) 2014 Elsevier GmbH. All rights reserved.
引用
收藏
页码:6678 / 6680
页数:3
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