2,769 People CCTV Person Re-Identification Dataset in Europe

CCTV re-id dataset

person re-identification data

pedestrian dataset

surveillance dataset

human re-id Europe

multi-camera reid dataset

pedestrian attributes data

computer vision reid

The 2,769 People CCTV Re-Identification Dataset in Europe provides high-quality pedestrian data for computer vision research. The data includes both males and females, with a racial distribution of Caucasian, Black, and Asian, and an age range from children to the elderly. The data diversity includes different age groups, different time periods, different cameras, and different body orientations and poses. Each person is annotated with rectangular bounding boxes and 15 body attributes. This data can be use for person re-identification, pedestrian tracking, surveillance analysis, and multi-camera AI models.

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Specifications

Data size

2,769 people, 1-25 cameras for each person

Population distribution

race distribution: 2,646 Caucasians, 47 Asians, 76 blacks; gender distribution: 1,091 males, 1,678 females; age distribution: mainly young and middle-aged

Collecting environment

department store

Data diversity

different age groups, different time periods, different cameras, different human body orientations and postures

Device

surveillance cameras, the resolution includes 960*576 and 1,440*1,616

Collecting angle

looking down angle

Collecting time

10:00-20:00

Data format

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

Annotation content

human body rectangular bounding boxes, 15 human body attributes

Accuracy rate

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%

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