Human Emotion Detection Using DeepFace and Artificial Intelligence

Abstract

An emerging topic that has the potential to enhance user experience, reduce crime, and target advertising is human emotion recognition, utilizing DeepFace and Artificial Intelligence (AI). The same feeling may be expressed differently by many individuals. Accurately identifying emotions can be challenging, in light of this. It helps to understand an emotion’s significance by looking at the context in which it is presented. Depending on the application, one must decide which AI technology to employ for detecting human emotions. Because of things like lighting and occlusion, using it in real-world situations can be difficult. Not every human emotion can be accurately detected by technology. Human–machine interaction technology is becoming more popular, and machines must comprehend human movements and expressions. When a machine recognizes human emotions, it gains a greater understanding of human behavior and increases the effectiveness of work. Text, audio, linguistic, and facial movements may all convey emotions. Facial expressions are important in determining a person’s emotions. There has been little research undertaken on the topic of real-time emotion identification, utilizing face photos and emotions. Using an Artificial Intelligence-based DeepFace approach, the proposed method recognizes real-time feelings from facial images and live emotions of persons. The proposed module extracts the facial features from an active shape DeepFace model by identifying 26 facial points to recognize human emotions. This approach recognizes the emotions of frustration, dissatisfaction, happiness, neutrality, and wonder. The proposed technology is unique, in that it implements emotion identification in real-time, with an average accuracy of 94% acquired from actual human emotions.

Keywords

• emotion detection
• age prediction
• gender prediction
• race prediction
• DeepFace
• deep learning