Eye-Controlled Mouse

Eye-Controlled Mouse is an innovative project that allows users to control the mouse cursor and perform clicks using just their eye movements. Utilizing real-time facial landmark detection through OpenCV and Mediapipe, this hands-free interaction offers a glimpse into advanced human-computer interaction, particularly useful for accessibility purposes.

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Key Features:

• Real-Time Eye Tracking: Detects and tracks key facial landmarks, specifically focusing on the eyes, to interpret gaze direction.
• Cursor Movement: Maps eye positions to screen coordinates, enabling mouse movement across the screen.
• Blink Detection for Clicks: Monitors blinking patterns to trigger mouse clicks when a significant eye closure is detected.
• Accurate Facial Landmark Recognition: Powered by Mediapipe's Face Mesh, which detects 468 key landmarks on the face with precision.

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How It Works:

1. Camera Input: The webcam captures the video feed, which is then processed frame-by-frame.
2. Face Mesh Processing: Mediapipe’s Face Mesh model extracts 468 landmarks from the face, refining key landmarks near the eyes for gaze tracking.
3. Cursor Mapping: The landmark coordinates are scaled and mapped onto the screen dimensions to move the mouse cursor accordingly.
4. Blink Detection: The distance between two specific eye landmarks is monitored. When the distance falls below a threshold (indicating a blink), a mouse click is triggered.

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Installation

1. Clone the Repository:

   git clone https://github.com/TejasUpadhyayy/Eye-controlled-Mouse.git

2. Install Dependencies:

   Install the required Python libraries:

   pip install opencv-python mediapipe pyautogui

3. Run the Script:

   Ensure your webcam is connected, then execute:

   python eye_controlled_mouse.py

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Requirements:

• Python 3.x
• OpenCV: For capturing and processing the video feed.
• Mediapipe: To detect and track facial landmarks.
• PyAutoGUI: For controlling mouse actions (movement and clicks).

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Customization:

• Threshold Adjustment: The blink detection threshold (0.004 in the script) can be fine-tuned for different lighting conditions or camera setups to avoid false positives.
• Screen Resolution: The script automatically scales the cursor movement based on screen resolution, but this can be adjusted in the code for custom resolutions.

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Applications:

• Accessibility: Provides hands-free control for individuals with mobility impairments.
• Human-Computer Interaction: Offers a novel interface for interacting with computers through gaze control.
• Eye-Tracking Research: Can serve as a foundation for more advanced gaze-tracking and eye-movement analytics systems.

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Future Enhancements:

• Right-Click Support: Introducing right-click functionality based on longer blinks or other facial cues.
• Multi-User Calibration: Implementing user-specific calibration for enhanced precision.
• Eye Gesture Recognition: Expanding the system to recognize complex eye gestures for more detailed control.

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Contact Me:

For any queries, suggestions, or collaboration opportunities, feel free to reach out:

• Email: [tejas.initiate@gmail.com]
• LinkedIn: Your LinkedIn Profile