OpenPose: Open-source Real-time Multi-person Key point and Pose Detection Program
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh.
Features
- Whole-body 3D Pose Reconstruction and Estimation
- Unity Plugin
- Whole-body (Body, Foot, Face, and Hands) 2D Pose Estimation
- Runtime Analysis
- 2D real-time multi-person keypoint detection
- 2x21-keypoint hand keypoint estimation
- 3D triangulation from multiple single views
- Unity Plugin
- Runtime Analysis
- Calibration toolbox: Estimation of distortion, intrinsic, and extrinsic camera parameters.
- Synchronization of Flir cameras handled.
- Single-person tracking
- Python API
- C++ API
Input
OpenPose supports image, video, webcam, Flir/Point Grey, IP camera, and support to add your own custom input source (e.g., depth camera).
Supported platforms
- Windows
- Linux (Ubuntu)
- macOS
Hardware compatibility
CUDA (Nvidia GPU), OpenCL (AMD GPU), and non-GPU (CPU-only) versions.
License
OpenPose is freely available for free non-commercial use, and may be redistributed under these conditions. Please, see the license for further details. Interested in a commercial license? Check this FlintBox link. For commercial queries, use the Contact section from the FlintBox link and also send a copy of that message to Yaser Sheikh.