Facial Expression Recognition using Support Vector Machine (SVM) and Convolutional Neural Network (CNN)

Authors

  • Afeefa Muhammed Student, Department of Electronics and Communication Engineering, Musaliar College of Engineering, Trivandrum, India
  • Ramsi Mol Student, Department of Electronics and Communication Engineering, Musaliar College of Engineering, Trivandrum, India
  • L. Revathy Vijay Student, Department of Electronics and Communication Engineering, Musaliar College of Engineering, Trivandrum, India
  • S. S. Ajith Muhammed Assistant Professor, Department of Electronics and Communication Engineering, Musaliar College of Engineering, Trivandrum, India
  • A. R. Shamna Mol Associate Professor, Department of Electronics and Communication Engineering, Musaliar College of Engineering, Trivandrum, India

Keywords:

Biometric markers, Computer vision, Convolutional neural network, Kernel trick, Machine learning, Support vector machine

Abstract

Facial expression is an important mode of non-verbal conversation among people. It is really a speedy growing and an evergreen research field in the region of computer vision, artificial intelligence and automation. Facial expressions can be recognized by training images. There are some limitations such as noise in the presently available emotion recognition techniques. This paper proposes a facial expression recognition method based on Support Vector Machine (SVM). It also adopts Convolutional Neural Network (CNN) for image training. SVM follows a technique called kernel trick to transform the data. SVM performs better than other existing techniques, and there by improves the overall performance of facial expression recognition.

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Published

08-09-2020

How to Cite

[1]
A. Muhammed, R. Mol, L. R. Vijay, S. S. A. Muhammed, and A. R. S. Mol, “Facial Expression Recognition using Support Vector Machine (SVM) and Convolutional Neural Network (CNN)”, IJRESM, vol. 3, no. 8, pp. 574–577, Sep. 2020.

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Articles