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. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or 25-keypoint body/foot keypoint estimation, including 6 foot keypoints. Runtime invariant to number of detected people. 2x21-keypoint hand keypoint estimation. Runtime depends on number of detected people. 70-keypoint face keypoint estimation. Runtime depends on number of detected people. Input: Image, video, webcam, Flir/Point Grey, IP camera, and support to add your own custom input source (e.g., depth camera).

Features

  • Whole-body 3D Pose Reconstruction and Estimation
  • Unity Plugin
  • Runtime Analysis
  • 2D real-time multi-person keypoint detection
  • 2x21-keypoint hand keypoint estimation
  • 3D triangulation from multiple single views

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

C++

Related Categories

C++ Libraries, C++ Machine Learning Software, C++ Computer Vision Libraries, C++ Object Detection Models

Registered

2022-07-28