Draw hand and pose landmarks on live webcam feed
Synthpose Markerless MoCap VitPose
Estimate and visualize 3D body poses from video
Mediapipe, OpenCV, CVzone simple pose detection
Small Space to test ViTPose
Duplicate this leaderboard to initialize your own!
Create a video using aligned poses from an image and a dance video
Analyze images to detect human poses
A visual scorer of two dance videos
Detect poses in real-time video
Analyze body and leg angles in images
Detect human poses in images
Detect and label poses in real-time video
Landmark Tracking is an AI-powered pose estimation tool that allows users to draw hand and pose landmarks on a live webcam feed. It provides real-time tracking and visualization of key points on the body, hands, or face, enabling applications in gesture recognition, fitness tracking, and more.
• Real-time Tracking: Processes video feed in real-time for immediate landmark detection.
• Multi-Mode Support: Capable of tracking hands, body, and face landmarks.
• Customizable Visualization: Users can adjust how landmarks are displayed.
• Cross-Platform Compatibility: Works on various operating systems.
• Lightweight Design: Optimized for low resource consumption.
• Integration Friendly: Can be embedded into larger applications.
What devices are supported by Landmark Tracking?
Landmark Tracking is compatible with most modern webcams and runs on Windows, macOS, and Linux systems.
Can I customize the appearance of landmarks?
Yes, users can adjust colors, sizes, and other visual properties of landmarks to suit their preferences.
Is Landmark Tracking suitable for real-time applications?
Absolutely! It is optimized for real-time performance, making it ideal for interactive and dynamic applications.