Face Tracking Device with Python and Arduino

Overview

This project is a real-time face tracking system that uses Python and OpenCV for face detection and Arduino for camera movement. The system captures a video feed, detects faces, and moves a camera accordingly using servo motors.

Features

• Real-time face detection using OpenCV's Haar Cascade Classifier
• Serial communication between Python and Arduino
• Camera movement using servo motors based on face position
• Adjustable sensitivity and movement parameters

Required Components

• Arduino UNO
• 2x Servo Motors (e.g., Tower Pro SG90)
• Web Camera
• Python & OpenCV libraries
• Haar Cascade file for face detection

Installation and Setup

1. Install Dependencies

Make sure you have Python installed. Then, install the required libraries:

pip install opencv-python pyserial numpy

2. Setup the Arduino

Upload the Arduino sketch (Cameracontol.ino) to your Arduino board using the Arduino IDE.

3. Run the Python Script

Place the haarcascade_frontalface_default.xml file in the same directory as main.py and run the script:

python main.py

How It Works

1. The webcam captures video frames.
2. OpenCV detects faces in real-time.
3. The Python script sends position commands (L, R, U, D, S) to the Arduino over a serial connection.
4. The Arduino moves the servos to adjust the camera's orientation.

Code Overview

Python (main.py)

• Reads frames from the webcam.
• Converts frames to grayscale.
• Detects faces and determines their position.
• Sends movement commands (L, R, U, D) to Arduino based on face position.

Arduino (Cameracontol.ino)

• Receives commands from Python via serial communication.
• Controls servo motors to adjust camera direction.

Future Improvements

• Implementing deep learning-based face tracking for better accuracy.
• Adding support for multiple face tracking.
• Using a pan-tilt camera module for smoother movement.

Author

Developed by Mohamed Bouchenti. Contributions and suggestions are welcome!