Deep Learning-Based System for Real-Time Face Tracking and Expression Recognition

Facial expressions play a crucial role in human communication by conveying emotions and messages without using words. They are a vital form of non-verbal communication that complements verbal communication. With the advent of artificial intelligence and machine learning, there has been an increase in the number of datasets and algorithms related to facial expressions. It has become an essential topic to explore automatic face tracking, expression recognition, and personalized feedback for different expressions. In this paper, we propose a real-time system that can track faces, recognize expressions, and provide distinct feedback based on the detected expressions. We present experimental results to demonstrate the effectiveness and feasibility of our proposed system.