Emoji Generation Using Facial Emotion Classifier

Abstract

Face expressions are an intrinsic aspect of nonverbal communication and play a significant role in Human Computer Interaction. The formation of facial emoticons is a human-computer interaction device. Emoji generation in real time based on a person's facial expression has always been difficult. Human social conversations depend on facial expressions. Since the world is becoming more technologically sophisticated day in day out, there are more interactive encounters, such as text messages, than physical ones. Emoticons promote virtual social interaction by reducing the amount of words exchanged. This paper describes an Emoji generation methodology based on Facial Expression Recognition (FER) and Convolutional Neural Networks (CNN) coupled with Machine Learning and Deep Learning. This CNN-based model can be put to work to evaluate feelings as users watch movie trailers or video lessons, as well as to help people with autism regulate their emotions.