This project implements a real-time facial recognition and behavioral analysis system. It is designed to identifying emotions and detecting potential suspicious activities (malpractice) in examination settings.
The system uses:
- Facial Expression Recognition (FER): To detect emotions like angry, happy, sad, neutral, etc.
- Object Detection (YOLOv8): To detect unauthorized objects like mobile phones.
✔ Live Dashboard: A modern web-based interface for monitoring. ✔ Expression Analysis: Real-time classification of user emotions. ✔ Malpractice Detection: Automatically flags "Cell Phone" usage with red bounding boxes. ✔ Session Stats: Tracks session time and activity.
- Backend: Python, Flask, OpenCV
- AI/ML: FER (Facial Expression Recognition), Ultralytics YOLOv8
- Frontend: HTML5, CSS3 (Modern Dark UI)
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Install Dependencies:
pip install -r requirements.txt
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Run the Application:
python app.py
Or simply double-click
run.bat. -
Open Browser: Navigate to
http://localhost:5000to view the dashboard.
I have done a complete research about on AI Pioneering Ethical, Analytical and Real time Emotional Recognition in Dynamic Human Expressions, which has been published in IEEE in the journal of ICCCDSAI 2025 (DOI: 10.1109/ICDSAAI65575.2025.11011864). I have included my extended research on this topic and project which i had later upscaled it.