Skeletal annotation involves detecting, associating, and tracking semantic keypoints. The dataset effectively solves the tasks of motion capture and recognition of human poses.

Pose Estimation Annotation

Ability of a machine to interpret, analyze, and understand visual data
Computer Vision
Detection and recognition the shape and pose of a human body on the image
Body Recognition
Process of identifying important poionts within an object on the image
Keypoint Detection
Highlighting objects in photos to train systems to recognize and interpret them
Data Labeling
Sports Medicine
Technologies that aid in preventing sports injuries and analyses training processes
2 000
2 weeks
project duration
annotation attributes
Each person is annotated with a Bounding-Box and 18 key points
Full-length photos of people are collected using parsing from open sources
Each image from the PE folder is accompanied by an XML annotation in the file annotations.xml specifying the coordinates of the key points.
The coordinates (x, y) and the “Assumed location” are marked for each point
Labeled body parts
Left elbow
Left wrist
Right shoulder
Right hip
Right elbow
Right knee
Right wrist
Right foot
Left shoulder
Left hip
Left knee
Left foot
Right eye
Left eye
Right ear
Left ear
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