This project demonstrates a hands-free cursor control system using eye movement. The system captures video through a webcam and processes the frames using OpenCV to detect the face and eyes. The pupil position is tracked to determine gaze direction, and the cursor movement is controlled using the PyAutoGUI library.
This project demonstrates a hands-free cursor control system using eye movements. The system captures video through a webcam and processes the frames using OpenCV to detect the user's face and eyes. The pupil position is tracked to determine gaze direction, and the cursor movement is controlled using the PyAutoGUI library.
The project is implemented using Python and computer vision techniques to enable real-time eye tracking and cursor control. Eye blinking can also be used as a clicking mechanism. This allows users to interact with the computer without using a physical mouse or keyboard.
This technology is especially useful for improving accessibility for physically disabled individuals and demonstrates the potential of eye-tracking systems in human-computer interaction.
- Python
- OpenCV
- MediaPipe
- PyAutoGUI
- Real-time face detection
- Eye and pupil tracking
- Cursor movement using eye direction
- Blink detection for mouse click
- Hands-free computer interaction
- Clone the repository
- Install required libraries
pip install -r requirements.txt
- Run the program
python eyeball_cursor.py
Shivani Jella
B.Tech – Information Technology
2025 Graduate