Face Emotion Recognition using Convolution Neural Network

Facial Expression has a significant role in every aspect of human life, either it can be for a communication purpose or to improve mental health, or to perceive the state of mind of a person. Even though there are many languages spoken worldwide by humans to communicate with each other which varies with the factors such as different community, different religion or different countries, etc., but sometimes when there are no words left for communication the facial expression is the one which comes into the picture and enhances the communication. The Face Emotion Recognition System has benevolence in the research and development industry. The systems that can detect the face and its features in the form of different emotions gives a rise to the terminology of Human Computer Interaction, in real life where the computers have superpowers to interact with humans. Humans socially interact with each other via emotions when communicating through words is not possible. In this research paper, we have discussed an approach of how does a system works that recognize Facial emotion using a Convolution Neural Network. A convolution Neural Network is said to be a best suited Neural Network for Pattern Recognition and Classification. Convolution Neural Network has an advantage, in which it reduces the dimension for large resolution images, without losing the quality of the image. Convolution Neural Network also captures and predicts features from Non-Frontal Face Images. This system can be useful for Sentimental Analysis, Business Analysis i.e. can be useful for getting a person's review on a certain product, in Automated Driving Cars, for the treatment of Autism Spectrum Disorder and many more. The primary focus is to conceptually understand the working of Convolution Neural Network for Face Emotion Recognition.