Facial Emotion Recognition
Facial Emotion Recognition (FER) for rehabilitation was our final year college group project, where we concentrated on refining the accuracy of various existing ML models. We integrated the model with hardware, such as an LED grid panel through Arduino, to visualize emotions as pixelated emojis using LEDs. Additionally, we employed a MERN-based website to track the metrics of detected emotions and conduct analysis.
KerasTensorflowPySerialOpencvScikitArduinoReactNodeExpressMongoDBFigma
Features
- Improved Accuracy of ML Model
- Integration with Hardware Devices
- Emotion Metrics Tracking
- Full-Stack Integration
- Real-Time Emotion Analysis
- User Interface Design
- Collaborative Development Process
Screenshots
