Face Emotion Detection Comparative Study Using Deep Learning

Abstract

People usually express their feelings and communicate with each other through facial emotion. Through face emotion detection we can easily understand the language of a person’s mind. Generally, face emotion detection is used in many cases. Among them, it is usually used by the police to catch criminals. Doctors often use face emotion detection to monitor a patient’s condition. Sometimes it is used in super shops to find out special customers so that they can give them special discounts. Here we detect face emotion using deep learning. There are two types of algorithms we use here. The algorithms are CNN and VGG16.We are collecting dataset from kaggle. Then we are preprocessing the dataset. Then we apply an algorithm in this dataset and find which algorithm can get better accuracy. Usually we can easily detect people’s emotions through CNN algorithm and VGG16 algorithm. Here we compare the two algorithms and find out which algorithm works better. Usually the two algorithms produce two different accuracy. Using face emotion detection the number of crimes in the society will decrease. it provides more security in society. Many researchers have research on it. We will use it to detect human face emotions and open it in the future so that everyone can use it and bring better results.