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tracking.js

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1,443
JavaScript

Project Description

A modern approach for Computer Vision on the web

tracking.js: A modern approach for Computer Vision on the web

Project Title

tracking.js — A Modern Approach for Real-Time Computer Vision on the Web

Overview

Tracking.js is a JavaScript library that brings computer vision algorithms into the browser environment, enabling real-time tracking of colors, faces, and objects. It stands out for its lightweight core (~7 KB) and intuitive interface, making it a powerful tool for developers looking to integrate computer vision capabilities into their web applications.

Key Features

  • Real-time color tracking and face detection
  • Lightweight core (~7 KB) for fast performance
  • Intuitive interface for easy integration
  • Supports HTML5 <canvas>, <video>, and <img> elements

Use Cases

  • Web developers implementing interactive features that require real-time object or color tracking
  • Applications in augmented reality, where real-time tracking is essential for overlaying digital content onto the real world
  • Security and surveillance systems that require real-time face detection

Advantages

  • Lightweight and fast, making it suitable for real-time applications
  • Easy to integrate into existing web projects
  • Supports a wide range of browsers, including IE 9+, Chrome, Firefox, Opera, and Safari

Limitations / Considerations

  • Browser support may vary when requesting user's camera, relying on the getUserMedia API
  • The library is still under development, with planned features like optical flow, face recognition, and pose estimation not yet implemented

Similar / Related Projects

  • OpenCV.js: A JavaScript port of the popular OpenCV library, offering a broader range of computer vision algorithms but with a larger footprint.
  • TensorFlow.js: A library for machine learning in the browser, which can be used for computer vision tasks but focuses more on deep learning models.

Basic Information


📊 Project Information

🏷️ Project Topics

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📚 Documentation


This article is automatically generated by AI based on GitHub project information and README content analysis

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Project Information

Created on 6/18/2012
Updated on 11/12/2025