10,034 People - Re-ID Data in Surveillance Scenes

Surveillance scenes

Re-ID

multiple time periods

multiple ages

human body rectangular bounding boxes

attributes annotation

10,034 People - Re-ID Data in Surveillance Scenes. The data includes supermarket (inside supermarket and at the gate of the supermarket) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 15 attributes of human body were annotated.The data can be used for re-id and other tasks.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Data size

10,034 people

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

supermarket (inside supermarket and at the gate of the supermarket)

Data diversity

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

Device

surveillance cameras, the image resolution is 1,920*1,080

Collecting time

8:00-22:00

Image parameters

the video data is in .mp4 format, the image data is in .jpg format, the annotation file is in .json format

Annotation content

human body rectangular bounding boxes, 15 human body attributes

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 attributes is over 97%

Recommended Dataset

65 People –15,204 Videos of Sports and Fitness Video Data

65 People –15,204 Videos of Sports and Fitness Video Data. The data collection scene is indoor scenes. The race distribution is Asian, black and Caucasian; the age distribution is young and middle-aged people. The collection device is IR and RGB cameras. The dataset diversity includes different races, different age groups, different shooting angles, different collection distances, different human body orientations, different costumes and various fitness actions. The data can be used for tasks such as human behavior recognition and human segmentation in fitness scenes.

Sports and fitness IR and RGB cameras human behavior recognition human segmentation fitness scenes.

11,130 People - Re-ID Data in Real Surveillance Scenes

11,130 People - Re-ID Data in Real 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. This data can be used for re-id and other tasks.

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

189 Videos-Electric Bicycle Entering Elevator Data

189 Videos-Electric Bicycle Entering Elevator Data，the total duration is 1 hour 58 minutes 40.72 seconds. The data covers different types of elevators, different types of electric bicycles, different time periods. The data can be used for tasks such as electric bicycle detection, electric bicycle recognition .

different types of elevators different types of electric bicycles different types of non-electric bicycles different time periods

5,808 People - Human Pose Recognition Data

5,808 People - Human Pose Recognition Data. This dataset includes indoor and outdoor scenes.This dataset covers males and females. Age distribution ranges from teenager to the elderly, the middle-aged and young people are the majorities. The data diversity includes different shooting heights, different ages, different light conditions, different collecting environment, clothes in different seasons, multiple human poses. For each subject, the labels of gender, race, age, collecting environment and clothes were annotated. The data can be used for human pose recognition and other tasks.

Different shooting heights different ages different light conditions different collecting environment clothes in different seasons multiple human poses

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

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.

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

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes. The data includes indoor (shopping mall) and outdoor (street, the gate of shopping mall and square) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 19 attributes of human body were annotated. The data can be used for person attributes recognition.

indoor and outdoor scenes human body bounding boxes appendage bounding boxes surveillance camera multiple age groups human body attributes

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

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.

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

40 People – Safety Dressing Collection Data

40 People – Safety Dressing Collection Data. Each subject collects 24 videos, each video lasts about 30 seconds. The gender distribution includes male and female, the age distribution is young and middle-aged. Collecting scenes include 2 indoor scenes and 2 outdoor scenes. The collecting angles are looking down angle, looking up angle. The data diversity includes multiple scenes, multiple actions, multiple angles, multiple safety dressing equipment. The data can be used for tasks such as detection and recognition of safety dressing for power personnel.

Safety dressing indoor scene outdoor scenes multiple scenes multiple actions multiple angles multiple safety dressing equipment detection and recognition of safety dressing for power personnel