Virtual Booth

This project presents a vision-based emotion recognition system designed to support mental health professionals by identifying patients' emotional states through facial micro-expressions. Traditional self-reporting often overlooks subtle emotional cues, leading to miscommunication or undetected distress. Leveraging computer vision and deep learning, the system analyzes real-time input from webcams or smartphones to recognize emotions non-invasively. A key deliverable is a functional prototype that enhances clinical communication. Compared to existing tools, it offers greater sensitivity, accessibility, and contextual accuracy. This initiative aligns with Sustainable Development Goal 3 by improving emotional care and well-being, especially in underserved or high-stress environments.