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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 7
2213-2219

TP-FER：facial expression recognition method of tri-path networks based on optimal convolutional neural network

Gao Jingwen1,2
Cai Yongxiang1,2
He Zongyi2
1. State Key Laboratory of Geo-Information Engineering, Xi'an 710054, China
2. School of Geosciences, Yangtze University, Wuhan 430100, China
DOI: 10.19734/j.issn.1001-3695.2020.07.0263

Abstract

Facial features play different functions in expressing different emotions, the only use of convolutional neural network for feature extraction and expression recognition of facial features may not lead to enough focus on the key feature information of facial expressions. However, the feature information only extracting from the key parts such as eyes or mouth may not be sufficient. This paper proposed a facial expression recognition method of tri-path networks based on the optimal convolutional neural network called TP-FER. Based on the convolutional neural network, this method used three input channels to focus on the face, eyes and mouth regions respectively for feature extraction and expression discrimination. Then it used the fusion technology based on the decision layer to make the final decision. At last, it adopted relative majority voting method based on the recognition results of the three channels to obtain the overall optimal recognition rate. This paper conducted several experiments on JCK+dataset and self-built dataset with this method. The results show that the overall expression recognition rate is improved in both datasets. This method can make full use of the different channel characteristics that focus on not only the key features such as eyes and mouth but also the comprehensive information of the whole face, and improve the expression recognition rate effectively. In addition, it can also provide data support for neuropsychological related research.

Foundation Support

地理信息工程国家重点实验室开放基金资助项目(SKLGIE2017-M-4-6)
国家自然科学基金青年基金资助项目(41701537)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.07.0263
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 7
Section: Technology of Graphic & Image
Pages: 2213-2219
Serial Number: 1001-3695(2021)07-056-2213-07

Publish History

[2021-07-05] Printed Article

Cite This Article

高静文, 蔡永香, 何宗宜. TP-FER：基于优化卷积神经网络的三通道人脸表情识别方法 [J]. 计算机应用研究, 2021, 38 (7): 2213-2219. (Gao Jingwen, Cai Yongxiang, He Zongyi. TP-FER：facial expression recognition method of tri-path networks based on optimal convolutional neural network [J]. Application Research of Computers, 2021, 38 (7): 2213-2219. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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