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Review on Emotion Recognition Using Facial Expressions

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  • Abozar Atya Mohamed Atya

    (Sudan Technological University, Sudan)

  • Khalid Hamid Bilal

    (University of Science &Technology, Sudan)

Abstract

The advent of artificial intelligence technology has reduced the gap between humans and machines as equips man to create more near-perfect humanoids. Facial expression is an important tool to communicate one’s emotions as a non-verbally overview of emotion recognition using facial expressions. A remarkable advantage of such a technique recently improved public security through tracking and recognizing, thus led to the high attention to keep up the scientific research in the field. The approaches used for facial expression include classifiers like Support Vector Machine (SVM), Artificial Neural Network (ANN), Convolution Neural Network (CNN), Active Appearance and Machine learning which all used to classify emotions based on certain parts of interest on the face like lips, lower jaw, eyebrows, cheeks and many more. By comparison, the reviews have shown that the average accuracy of the basic emotion ranged from 51% up to 100%, whereas carrying through 7% to 13% in the compound emotions, hence indicated that the indispensable emotion is much comfortable to recognize.

Suggested Citation

  • Abozar Atya Mohamed Atya & Khalid Hamid Bilal, 2021. "Review on Emotion Recognition Using Facial Expressions," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 5(3), pages 1-4, May.
    • Handle: RePEc:epw:ejece0:v:5:y:2021:i:3:id:19322
    DOI: 10.24018/ejece.2021.5.3.322
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