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🌍 Live Earth Simulator

Project Overview

Live Earth Simulator is an interactive web-based application that enables users to explore and control a realistic 3D Earth model using natural hand gestures captured through a live webcam feed. The system combines computer vision, real-time graphics rendering, and web technologies to create a futuristic touchless interaction experience.

Built using Python, Flask, MediaPipe, and Three.js, the project demonstrates the practical implementation of Human-Computer Interaction (HCI), allowing users to rotate, move, and scale a 3D Earth model in real time without using a mouse or keyboard.


Features

  • Live Camera Preview
  • Real-Time Hand Tracking
  • AI-Powered Gesture Recognition
  • Interactive 3D Earth Visualization
  • Earth Rotation Control
  • Earth Position Movement
  • Pinch Gesture Scaling
  • Touchless User Interaction
  • Real-Time Rendering
  • Responsive Web Interface
  • Modern UI/UX Design
  • Cross-Platform Browser Support

Technologies Used

  • Python
  • Flask
  • HTML5
  • CSS3
  • Bootstrap 5
  • JavaScript (ES6)
  • MediaPipe Hands
  • Three.js
  • Computer Vision
  • Human-Computer Interaction (HCI)

Project Structure

Live-Earth-Simulator/

├── app.py

├── requirements.txt

├── static/

│ └── js/

│ └── app.js

├── templates/

│ ├── base.html

│ ├── index.html

│ ├── live_preview.html

│ ├── about.html

│ └── contact.html

├── .gitignore

└── README.md


Installation Steps

1. Clone the Repository

git clone https://github.com/yourusername/live-earth-simulator.git

cd live-earth-simulator

2. Create Virtual Environment

python -m venv venv

3. Activate Virtual Environment

Windows:

venv\Scripts\activate

Linux/Mac:

source venv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

5. Run the Application

python app.py

6. Open Browser

http://127.0.0.1:5000

System Workflow

Camera Initialization

  • User opens the Live Preview page.
  • Browser requests webcam access.
  • Live video feed is activated.
  • Hand tracking begins automatically.

Hand Tracking

  • MediaPipe detects hand landmarks.
  • Real-time hand positions are tracked.
  • Gesture patterns are analyzed.
  • User actions are identified.

Earth Interaction

  • Palm movement controls Earth position.
  • Horizontal hand movement rotates the Earth.
  • Pinch gesture scales the Earth model.
  • Real-time updates are rendered using Three.js.

Core Modules

Hand Tracking Module

  • Webcam Access
  • Hand Landmark Detection
  • Gesture Recognition
  • Motion Analysis

3D Visualization Module

  • Earth Rendering
  • Real-Time Animation
  • Object Scaling
  • Rotation Management

Gesture Control Module

  • Movement Detection
  • Rotation Control
  • Zoom Functionality
  • Gesture Mapping

User Interface Module

  • Live Camera Preview
  • Interactive Controls
  • Responsive Layout
  • Modern User Experience

Requirements

Flask
MediaPipe
OpenCV-Python
Three.js
NumPy
Bootstrap 5

Install all requirements using:

pip install -r requirements.txt

Future Enhancements

  • Voice Command Integration
  • AR/VR Support
  • Multi-Hand Gesture Recognition
  • Custom Gesture Configuration
  • Cloud Deployment
  • Performance Analytics
  • Mobile Optimization
  • AI-Based Gesture Personalization

Use Cases

  • Educational Demonstrations
  • Geography Learning
  • Astronomy Visualization
  • Human-Computer Interaction Research
  • AR/VR Prototyping
  • Technical Project Demonstrations
  • Academic Presentations
  • Portfolio Showcases

Author

Developed by: Barnali Bhowmik


License

This project is created for educational and learning purposes. Feel free to modify and improve it as needed.

⭐ If you find this project useful, please give it a star.

🔥 Live Earth Simulator showcases the power of modern web technologies combined with AI to create immersive, futuristic user experiences.

About

Live Earth Simulator is an AI-powered interactive web application developed using Python, Flask, MediaPipe, and Three.js that allows users to control and explore a realistic 3D Earth model using real-time hand gestures captured through a webcam. The system utilizes computer vision and gesture recognition technologies to provide touchless interactio

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