Real-time intelligent facial expression recognition system

M. Rizwan Tanweer; M. Hassan Tanveer; Asif A Mayo; Qurat-ul-Ain; Jawwad Ahmad

doi:10.31645/JISRC.22.20.2.4

Author(s)

M. Rizwan Tanweer Department of Decision Sciences, Karachi School of Business and Leadership,Karachi,Pakistan

M. Hassan Tanveer Department of Robotics & Mechatronics, Engineering, Kennesaw State University,Marietta,USA

Asif A Mayo Department of Computer Engineering, FEST, Hamdard University,Karachi,Pakistan

Qurat-ul-Ain Department of Computer Engineering, FEST, Hamdard University,Karachi,Pakistan

Jawwad Ahmad Electrical Engineering Department, Usman Institute of Technology,Karachi,Pakistan

Abstract

Facial expression plays an important role in conveying the non-verbal cues of any person. In this research, a real-time detection of emotions has been performed by training the model into different data sets and then emotional state of a person is displayed. The aim of the project is to recognize human emotions in real-time which are based on their facial expressions. Tremendous work has been done in recognizing emotions using facial expression but little work is done on recognizing eight emotions in real-time. For this purpose, a realtime system to judge eight emotions using facial expression has been designed. Further, the performance of the proposed method is evaluated by using trained database using Convolution Neural Network (CNN) and Support vector machines (SVM). Experimental results and prototype show the accuracy of detected emotions in real-time. This research work has been conducted to recognize human emotions in Real-time and increased the accuracy for CNN algorithm. The study is concluded which results in recognition of eight universal emotions; neutral, happy, sad, anger, disturbed, fear, surprised, nervous in real time by the proposed system.

Publication Details

Page(s) 24-31

DOI 10.31645/JISRC.22.20.2.4

Published Journal: Journal of Independent Studies and Research Computing, Volume: 20, Issue: 2, Year: 2022

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Keywords

Facial expression recognition, Machine learning, Artificial intelligence, Computer vision