OpenPose

  • AI Model

OpenPose represents the first real-time multi-person system to jointly detect human body, hand, and facial keypoints (in total 130 keypoints) on single images.

Features

Functionality:

2D real-time multi-person keypoint detection:

15 or 18 or 25-keypoint body/foot keypoint estimation. Running time invariant to number of detected people.

2x21-keypoint hand keypoint estimation. Currently, running time depends on number of detected people.

70-keypoint face keypoint estimation. Currently, running time depends on number of detected people.

3D real-time multi-person keypoint detection:

3-D triangulation from multiple single views.

Synchronization of Flir cameras handled.

Compatible with Flir/Point Grey cameras, but provided C++ demos to add your custom input.

Calibration toolbox:

Easy estimation of distortion, intrinsic, and extrinsic camera parameters.

Input: Image, video, webcam, Flir/Point Grey and IP camera. Included C++ demos to add your custom input.

Output: Basic image + keypoint display/saving (PNG, JPG, AVI, …), keypoint saving (JSON, XML, YML, …), and/or keypoints as array class.

OS: Ubuntu (14, 16), Windows (8, 10), Mac OSX, Nvidia TX2.

Others:

Available: command-line demo, C++ wrapper, and C++ API.

CUDA (Nvidia GPU) and CPU versions.


Name

OpenPose

Description

OpenPose represents the first real-time multi-person system to jointly detect human body, hand, and facial keypoints (in total 130 keypoints) on single images.

Programming Language

Sub-Fields