Facial Expression Recognition Using Convolutional Neural Network

被引：18
|
作者：
Gan, Yijun [1 ]
机构：
[1] Ball State Univ, 2217 W Bethel Ave Apt 131, Muncie, IN 47306 USA
来源：
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON VISION, IMAGE AND SIGNAL PROCESSING (ICVISP 2018) | 2018年
关键词：
Facial Expression Recognition; CNN; FER2013;
D O I：
10.1145/3271553.3271584
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Facial expressions are part of human language and are often used to convey emotions. With the development of human-computer interaction technology, people pay more and more attention to facial expression recognition (FER) technology. Besides, in the domain of FER, human beings have made some progress. In this paper, we reviewed the development of FER: VGGNet, ResNet, GoogleNet, and AlexNet. Besides, we studied some ideas of CNN (Convolutional Neural Network), and we used FER2013, which is one of the most significant databases of human faces, as the dataset to be considered. Furthermore, we made some improvements based on the original methods of FER. By training the FER2013 dataset with different revised ways, the best result of accuracy we got is 0.6424. At last, we generated and summarized the progress and deficiencies in this study.
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页数：5
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