eduardolundgren/tracking.js
Tracking.js
tracking.js is a browser computer vision library written in JavaScript for performing real-time image analysis and object tracking directly within a web browser. It functions as a real-time object tracker, a color tracking tool, and a face detection utility.
The library enables the detection and monitoring of specific color ranges, human faces, and known visual patterns across consecutive video frames. It extracts visual features and descriptors from images to identify distinct landmarks for matching and tracking.
The project covers broad computer vision capabilities, including the ability to process image data through filters and transformations and the execution of real-time video tracking.
Features
- Web-Based Computer Vision - Provides a JavaScript library for performing computer vision and image segmentation directly within web browser environments.
- Color Tracking - Identifies and follows specific color ranges within a video stream or image in real time.
- Computer Vision Features - Extracts visual patterns and key points from image data to identify landmarks for tracking.
- Face Detection - Provides algorithms that identify human faces within image frames to determine their position and pose.
- Face Tracking - Detects human faces in video streams to determine position and pose for visual overlays.
- Image Processing - Provides essential image processing filters like grayscale and blurring to prepare data for analysis.
- Object Detection and Tracking - Detects and follows known shapes or patterns across frames to maintain a lock on target objects.
- Real-Time Object Detection - Uses computer vision algorithms to identify and follow objects or colors within live video streams.
- Feature Extraction - Extracts key points and descriptors to identify distinct landmarks for tracking movement and rotation.
- Object Tracking - Maintains persistent identity and spatial coordinates of objects across consecutive video frames.
- Color Segmentation - Provides color-range segmentation to isolate objects using RGB or HSV thresholds.
- Feature Extraction - Analyzes images to extract distinct landmarks and key points for matching and tracking.
- Colors - Detects and monitors specific color ranges to locate and follow colored objects in video.
- Color-Based Object Detection - Locates and monitors specific color ranges in images or video to track colored objects.
- Sequential Frame Processing - Implements a frame-by-frame processing loop for real-time video stream analysis.
- Spatial State Tracking - Calculates geometric centers and boundaries of visual blobs to maintain target identity across frames.
- Visual Landmark Extractors - Extracts visual features and descriptors from images to identify distinct landmarks for matching and tracking.
- Template Matching - Locates targets by comparing reference images against video frames using pixel correlation.
- Pixel-Level Image Manipulation - Implements real-time analysis by directly manipulating raw pixel arrays within an HTML5 Canvas element.
- AI & Machine Learning - Modern approach to computer vision on the web.
- Machine Learning and Vision - Computer vision for the web.
