Pose Estimation

Pose estimation is a computer vision technique that predicts the configuration of a person's or object's joints or parts in an image or video.

It involves detecting and tracking the position and orientation of these parts, usually represented as keypoints.

Pose estimation is widely used in applications such as motion capture, human-computer interaction, augmented reality, and robotics. The process typically involves training machine learning models on large datasets of annotated images to accurately identify and locate the keypoints.

Pose Estimation Related Models

Sr No	Model	Developer	Key Points	Source	License
1	MediaPipe	Google	Tracking 33 key points on the human body, offering cross-platform, customizable ML solutions	MediaPipe GitHub	Apache 2.0
2	Detectron2	Facebook AI Research	High-performance codebase for object detection and segmentation, including pose estimation	Detectron2 GitHub	Apache 2.0
3	OpenPose	Carnegie Mellon University	Detecting key points of the human body, including hand, facial, and foot	OpenPose GitHub	MIT
4	MoveNet	Google Research	Detecting 17 critical key points of the human body	MoveNet GitHub	Apache 2.0