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18,880 Images of 466 People - 3D Instance Segmentation and 22 Landmarks Annotation Data of Human Body

Human body instance segmentation
Human body landmarks
3D
Multiple poses
Multiple scenes

18,880 Images of 466 People - 3D Instance Segmentation and 22 Landmarks Annotation Data of Human Body. The dataset diversity includes multiple scenes, light conditions, ages, shooting angles, and poses. In terms of annotation, we adpoted instance segmentation annotations on human body. 22 landmarks were also annotated for each human body. The dataset can be used for tasks such as human body instance segmentation and human behavior recognition.

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SpecificationsSpecifications
Data size
466 people, the number of  images is 18,880
Race distribution
Asian
Gender distribution
233 males, 233 females
Age distribution
299 children and teenagers, 167 adults
Collecting environment
including indoor scenes and outdoor scenes
Data diversity
multiple scenes, light conditions, ages, shooting angles, and poses
Device
RealSense Depth Camera D435i
Data format
the image data format is .jpg and .png, the annotation file format are .json,the file format of camera parameters is .txt
Collecting content
3D images of various human body poses ((the rgb channel and depth channel have been registered))
Annotation content
instance segmentation annotation of human body , 22 landmarks annotation of human body
Accuracy
Accuracy requirement: the mask edge location errors in x and y directions are less than 3 pixels, which is considered as a qualified annotation;  Accuracy requirement of segmentation annotation: the annotation part (each part of mask) is regarded as the unit, the accuracy rate shall be more than 95%; Accuracy requirement of landmark annotation: the annotation part (each landmark) is regarded as the unit, the accuracy rate shall be more than 95%; Annotating accuracy = number of correct annotations / total number of annotations
Sample Sample
  • Waiting For Data
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