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5,521 People - Re-ID Data in Surveillance Scenes

Surveillance scenes
Re-ID
different age groups
different time periods
different shooting angles
different human body orientations and postures
clothing for different seasons
human body rectangular bounding boxes
attributes annotation

5,521 People - Re-ID Data in Surveillance Scenes. 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, clothing for different seasons. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. The data can be used for re-id and other tasks.

Paid Datasets
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
SpecificationsSpecifications
Data size
5,521 people, 36 images were annotated for each subject
Population distribution
population distribution: Asian; gender distribution: 2,522 males, 2,999 females; age distribution: 930 people under 18 years old, 3,156 people aged from 18 to 45 years old,  808 people aged from 46 to 60 years old, 627 people over 60 years old
Collecting environment
indoor scenes, outdoor scenes
Data diversity
different age groups, different time periods, different shooting angles, different human body orientations and postures, clothing for different seasons
Device
surveillance cameras
Collecting angle
looking down angle
Collecting time
day, night
Data format
the image data format is .jpg, .png, the annotation file format is .json
Annotation content
human body rectangular bounding boxes, 15 human body attributes; label the subject's gender, age, race, collecting scenes, clothing categories, camera ID, camera height
Accuracy
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 human attributes is over 97%; the accuracy of label annotation is not less than 97%
Sample Sample
  • Waiting For Data
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