Facial Movement Controlled Virtual Keyboard System

An open-source Human-Computer Interaction (HCI) project that uses facial landmarks and eye-blink detection to simulate keyboard input using only facial movements. This application enables users to select characters on a virtual keyboard through column scanning and blink detection — empowering hands-free communication and accessibility.

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Table of Contents

• Project Overview
• Features
• Getting Started
• Installation & Setup
• Usage
• Technologies Used
• Contributing
• Credits

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Project Overview

This project leverages OpenCV, dlib, and facial landmark detection to implement a virtual keyboard navigable using eye blinks and column-row scanning logic. It’s ideal for accessibility applications or touchless interfaces where traditional input methods are impractical.

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Features

✅ Real-time facial landmark detection ✅ Virtual keyboard grid with character highlighting ✅ Blink-controlled character selection ✅ Column-row scanning mechanism ✅ Works on standard webcam input

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Getting Started

Follow these steps to run the project locally on your machine.

1. Clone or Download the Repository

git clone https://github.com/vivekbargude/FaceBoard.git
cd FaceBoard

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Installation & Setup

2. Install Required Python Libraries

Make sure you have Python 3.6+ installed.

pip install opencv-python dlib numpy

💡 Note: Installing dlib may require CMake and Visual Studio Build Tools on Windows.

3. Download Pretrained Shape Predictor

Download the shape_predictor_68_face_landmarks.dat file from: 🔗 http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2

Extract it and place it in the desired location (update the path in the script accordingly):

predictor = dlib.shape_predictor("path_to/shape_predictor_68_face_landmarks.dat")

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Usage

4. Run the Application

python facial_keyboard.py

Make sure your webcam is connected and accessible.

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How It Works

1. Face Detection: Uses dlib to detect face and 68 facial landmarks.
2. Column Scanning: Columns are highlighted sequentially.
3. Blink to Select Column: When the user blinks, the currently highlighted column is selected.
4. Row Scanning: Rows in the selected column are scanned.
5. Blink to Select Character: Another blink selects the character, which is added to the text buffer.

Escape key ESC exits the program.

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Technologies Used

• Python 3.6+
• OpenCV – Real-time image processing
• dlib – Face detection and landmark estimation
• NumPy – Array operations

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Contributing

We welcome contributions to improve functionality and performance.

1. Fork the repo

2. Clone it:

   git clone https://github.com/vivekbargude/FaceBoard.git

3. Make your changes and test locally

4. Submit a pull request

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Credits

Developed by: Vivek Bargude

Inspired by accessibility challenges and advancements in facial gesture interfaces.

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