Development of Simulator to Recognize the Mood using Facial Emotion Detection

Abstract

Emotions make up a key feature of conduct in human beings which aids in communication. Non-verbal communication aids in deciphering verbal communication. Non-verbal communication includes body language, facial gestures, hand postures etc., out of which facial expressions give 55% effect of what is being communicated. Humans experience many emotions which have been classified into six main emotions i.e., Sadness, Happiness, Anger, Disgust, Fear, and Surprise. Humans have a spontaneous and innate ability to understand facial gestures and construe the emotion. The same activity proves to be a great challenge for computer systems. Analyzing the facial features and perceiving the emotions is difficult due to their inconsistency. Many fields are interested in detecting human emotions using systems. In this project, we are training the model on the FER 2013 dataset. The image of a person is captured in real-time and the percentage of emotions the person depicts is plotted using a bar graph.