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Real-Time Emotion Recognition Framework Based on Convolution Neural Network

  • Hanting Yang
  • Guangzhe ZhaoEmail author
  • Lei Zhang
  • Na Zhu
  • Yanqing He
  • Chunxiao Zhao
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 157)

Abstract

Efficient emotional state analyzing will enable machines to understand human better and facilitate the development of applications which involve human–machine interaction. Recently, deep learning methods become popular due to their generalization ability, but the disadvantage of complicated computation could not meet the requirements of real-time characteristics. This paper proposes an emotion recognition framework based on convolution neural network, which contains less number of parameters comparatively. In order to verify the proposed framework, we train a network on a large number of facial expression images and then use the pretrained model to predict image frame taken from a single camera. The experiment shows that compared to VGG13, our network reduces the parameters by 147 times.

Keywords

CNN Emotion recognition Image processing 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Hanting Yang
    • 1
  • Guangzhe Zhao
    • 1
    Email author
  • Lei Zhang
    • 1
  • Na Zhu
    • 1
  • Yanqing He
    • 1
  • Chunxiao Zhao
    • 1
  1. 1.Beijing University of Civil Engineering and ArchitectureBeijingChina

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