21,404 Images - Human Posture Detection Data in Home Scenes

Home scene

human posture detection

multiple scenes

multiple time periods

multiple collecting heights

multiple human body occlusions

multiple collecting distances

human body rectangular bounding boxes

21,404 images - human posture detection data in home scenes. The data scenes are 101 different indoor hone scenes. The gender distribution includes male and female, the age distribution is ranging from young to the elderly, the middle-aged and young people are the majorities. The data diversity includes multiple scenes, multiple time periods, multiple collecting heights, multiple human body occlusions, multiple collecting distances. For collection content, the human body postures data in different home scenes were collected, the human bodies were lying flat, lying on its side or lying on its stomach. For annotation, human body rectangular bounding boxes were annotated. The data can be used for tasks such as human body detection in home scenes.

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Specifications

Data size

21,404 images, one images includes one human body

Population distribution

gender distribution: male, female; age distribution: ranging from young to the elderly, the middle-aged and young people are the majorities; race distribution: Asian

Collecting environment

101 different indoor hone scenes

Data diversity

multiple scenes, multiple time periods, multiple collecting heights, multiple human body occlusions, multiple collecting distances

Device

surveillance camera, the resolution is 1,920*1,080 or 2,560*1,920

Collecting angle

looking down angle

Collecting height

1 meter, 1.5 meters, 2 meters

Collecting time

day, night

Collecting time

the image data format is .jpg, the annotation file format is .json or .xml

Collection content

collecting the human body postures data in different home scenes, the human bodies were lying flat, lying on its side or lying on its stomach

Annotation content

human body rectangular bounding boxes were annotated

Accuracy rate

the rectangular bounding box of human body is qualified when the deviation is not more than 3 pixels, and the qualified rate of the bounding boxes shall not be lower than 97%

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