Real-Time facial expression recognition based on cnn

Keng Cheng Liu, Chen Chien Hsu, Wei Yen Wang, Hsin Han Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we propose a method for improving the robustness of real-Time facial expression recognition. Although there are many ways to improve the accuracy of facial expression recognition, a revamp of the training framework and image preprocessing allow better results in applications. One existing problem is that when the camera is capturing images in high speed, changes in image characteristics may occur at certain moments due to the influence of light and other factors. Such changes can result in incorrect recognition of the human facial expression. To solve this problem for smooth system operation and maintenance of recognition speed, we take changes in image characteristics at high speed capturing into account. The proposed method does not use the immediate output for reference, but refers to the previous image for averaging to facilitate recognition. In this way, we are able to reduce interference by the characteristics of the images. The experimental results show that after adopting this method, overall robustness and accuracy of facial expression recognition have been greatly improved compared to those obtained by only the convolution neural network (CNN).

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on System Science and Engineering, ICSSE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages120-123
Number of pages4
ISBN (Electronic)9781728105253
DOIs
Publication statusPublished - 2019 Jul
Event2019 International Conference on System Science and Engineering, ICSSE 2019 - Dong Hoi City, Quang Binh Province, Viet Nam
Duration: 2019 Jul 202019 Jul 21

Publication series

NameProceedings of 2019 International Conference on System Science and Engineering, ICSSE 2019

Conference

Conference2019 International Conference on System Science and Engineering, ICSSE 2019
CountryViet Nam
CityDong Hoi City, Quang Binh Province
Period19/7/2019/7/21

Keywords

  • average weighting method
  • convolution neural network (CNN)
  • facial expression recognition

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

Fingerprint Dive into the research topics of 'Real-Time facial expression recognition based on cnn'. Together they form a unique fingerprint.

Cite this