Human Sentiment Analysis using Machine Learning & Image Processing

Abstract

Facial expressions reveal a great deal about a person's feelings. One of the most difficult aspects of interpersonal relationships is effectively reading facial emotions. Automatic emotion identification based on facial expression recognition has become a hot topic in domains including computer science, medicine, and psychology. For improved outcomes, HCI research communities employ an automated face expression recognition system. For the recognition of expressions in both static photos and real-time films, many feature extraction algorithms have been developed. Love, happiness, rage, fear, and sadness are all examples of human emotions. These photographs are quite diverse from one another, but they all show the same human emotion. In this study, we look into the prospect of utilising machine learning to predict an image's emotion. These kind of predictions can be employed in applications such as automatic tag predictions for social media photographs. Websites, as well as a buyer purchasing a product from a store or through a social media platform, can be useful for determining product quality.. Keywords:- Human Sentiment, Emotion, CNN, ten emotions, , RAFT.