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4,001 People Single Object Multi-view Tracking Data

Multi-view tracking

Surveillance scenes

Human body

Multiple scenes

4,001 People Single Object Multi-view Tracking Data, the data collection site includes indoor and outdoor scenes (such as supermarket, mall and community, etc.) , where each subject appeared in at least 7 cameras. The data diversity includes different ages, different time periods, different cameras, different human body orientations and postures, different collecting scenes. It can be used for computer vision tasks such as object detection and object tracking in multi-view scenes.

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

Specifications

Data size

4,001 people, about 385-2,779 images per person

Race distribution

Asian

Gender distribution

2,052 males, 1,949 females

Age distribution

from children to the elderly

Collecting environment

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

Data diversity

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

Device

surveillance cameras, the image resolution is not less 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

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%

Sample

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212 People – 48,000 Images of Multi-person and Multi-view Tracking Data

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10,114 People Multi-view Tracking Data

This data is a multi-view tracking data of 10,114 people in surveillance scenes. Surveillance scenes includes indoor and outdoor scenes. The data includes men and women of different ages. In terms of annotation, the human body bounding boxes, human body + riding object bounding boxes, and 21 human body attributes of tracking objects were annotated. This data can be used for human body multi-view tracking, Re-ID and other tasks.

Multi-view Cross-camera human body tracking Re-ID Re-ID

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4,001 People Single Object Multi-view Tracking Data

Multi-view tracking Surveillance scenes Human body Multiple scenes

Multi-view tracking

Surveillance scenes

Human body

Multiple scenes