Facial expression detection and classification using SVM, CNN and decision tree algorithm

A Adithya; H Anisa; J S Monika; Tina Susan Thomas; Ashwin Kumar

doi:10.53730/ijhs.v6nS4.9770

Authors

Adithya A
18it01@kcgcollege.com
Department of Information Technology, KCG College of Technology, Chennai, India
Anisa H Department of Information Technology, KCG College of Technology, Chennai, India
Monika J S Department of Information Technology, KCG College of Technology, Chennai, India
Tina Susan Thomas Department of Information Technology, KCG College of Technology, Chennai, India
Ashwin Kumar Senior Security Consultant, Genpact, India

Keywords:

facial expression, machine learning, human emotions, convolution neular networks, support vector machine, decision tree

Abstract

The human face is often used as a visual representation of information, which is why facial expression recognition is very important in terms of human-machine interaction. It can be used for various applications such as detecting mental disorders and understanding human behavior.Despite the advantages of facial expression recognition technology, the high recognition rate to be achieved by a computer is still challenging. Two commonly used methods are geometry and appearance . Machine learning methods like CNN, Decision tree and SVM were applied to identify the human emotions like happiness, fear, disgust, anger, surprise, sadness and neutrality.

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