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.
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