Emotion Recognition using Facial Biometrics

This project focuses on developing an AI-driven system to recognize human emotions through facial biometrics. The system utilizes computer vision and deep learning techniques to analyze facial expressions and classify emotions such as happiness, sadness, anger, surprise, and neutrality.

Key Features & Technologies Used:

- Facial Detection & Preprocessing: Uses OpenCV and deep learning models to detect and extract facial features.

- Deep Learning Model:Implemented using CNNs (Convolutional Neural Networks) trained on datasets like FER2013 or AffectNet.

- Real-Time Emotion Recognition:Processes video streams or images to classify emotions in real time.

- Integration with Applications: Can be used in gaming, customer experience analysis, mental health monitoring, and human-computer interaction.

This project demonstrates expertise in AI, computer vision, and biometrics, showcasing the ability to build intelligent systems that interpret human emotions.