Real-Time Intelligent Facial Expression Recognition System

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 real-time 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.