Recognition of Face Emotion using Convolutional Neural Network

  • Sastry* D
  • et al.
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Abstract

Recognition of face emotion has been a challenging task for many years. This work uses machine learning algorithms for both, a real-time image or a stored database image in the area of facial emotion recognition system. So it is very clear that, deep learning technology becomes important for Human-computer interaction (HCI) applications. The proposed system has two parts, real-time based facial emotion recognition system and also the image based facial emotion recognition system. A Convolutional Neural Network (CNN) model is used to train and test different facial emotion images in this research work. This work was executed successfully using Python 3.7.6 platform. The input Face image of a person was taken using the webcam video stream or from the standard database available for research. The five different facial emotions considered in this work are happy, surprise, angry, sad and neutral. The best recognition accuracy with the proposed system for the webcam video stream is found to be 91.2%, whereas for the input database images is found to be 90.08%.

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Sastry*, Dr. P. N., & Syed, M. S. (2020). Recognition of Face Emotion using Convolutional Neural Network. International Journal of Innovative Technology and Exploring Engineering, 9(9), 364–376. https://doi.org/10.35940/ijitee.i7033.079920

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