11,130 People – Real Surveillance Re-ID Dataset (Indoor & Outdoor)

human re-id dataset surveillance

large-scale person re-identification dataset

real surveillance re-id data

multi-scene human re-id dataset

person tracking and re-id dataset

human body attributes

re-id dataset

human re-id dataset

The data includes indoor scenes and outdoor scenes. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different shooting angles, different human body orientations and postures, seasonal clothing. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. This data can be used for re-ID, person tracking, AI/computer vision research in realistic surveillance environments and other tasks.

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Specifications

Data size

11,130 people, about 10-27 images per person

Population distribution

the race distribution is Asian, the gender distribution is male and female, the age distribution is from children to the elderly

Collecting environment

including indoor and outdoor scenes (such as supermarket, mall and residential area, etc.)

Data diversity

different ages, different time periods, different cameras, different human body orientations and postures, different ages collecting environment

Device

surveillance cameras, the image resolution is not less than 1,920*1,080

Data format

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

Annotation content

human body rectangular bounding boxes, 15 human body attributes

Quality Requirements

A 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%;Annotation accuracy of attributes is over 97%

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