Facial Smile Detection Using Convolutional Neural Networks

被引:0
|
作者
Dinh Viet Sang [1 ]
Le Tran Bao Cuong [1 ]
Do Phan Thuan [1 ]
机构
[1] Hanoi Univ Sci & Technol, Hanoi, Vietnam
来源
2017 9TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2017) | 2017年
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Facial expression analysis plays a key role in analyzing emotions and human behaviors. Smile detection is a special task in facial expression analysis with various potential applications such as photo selection, user experience analysis, smiling payment and patient monitoring. Conventional approaches often extract low-level face descriptors and detect smile based on a strong binary classifier. In this paper, we propose an effective architecture of Convolutional Neural Networks (CNNs) to detect smile in real-time speed with high accuracy. The experimental results show that our proposed network outperforms recent state-of-the-art methods.
引用
收藏
页码:136 / 141
页数:6
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