[{"@type":"PropertyValue","name":"Data size","value":"4,001 people, about 385-2,779 images per person"},{"@type":"PropertyValue","name":"Race distribution","value":"Asian"},{"@type":"PropertyValue","name":"Gender distribution","value":"2,052 males, 1,949 females"},{"@type":"PropertyValue","name":"Age distribution","value":"from children to the elderly"},{"@type":"PropertyValue","name":"Collecting environment","value":"including indoor and outdoor scenes (such as supermarket, mall and community, etc.)"},{"@type":"PropertyValue","name":"Data diversity","value":"different ages, different time periods, different cameras, different human body orientations and postures, different collecting scenes"},{"@type":"PropertyValue","name":"Device","value":"surveillance cameras, the image resolution is not less 1,920*1,080"},{"@type":"PropertyValue","name":"Data format","value":"the image data format is .jpg, the annotation file format is .json"},{"@type":"PropertyValue","name":"Annotation content","value":"human body rectangular bounding boxes"},{"@type":"PropertyValue","name":"Accuracy","value":"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%"}]
{"id":1231,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY230208001.png?Expires=2007353721&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=yxXljtYoH34z1wVHwpjlyUcE63E%3D","type1":"147","type1str":null,"type2":"148","type2str":null,"dataname":"Multi-view Person Tracking Dataset – 4,001 Subjects for Re-ID and Computer Vision Tasks","datazy":[{"title":"Data size","content":"4,001 people, about 385-2,779 images per person","desc":"Data size"},{"title":"Race distribution","content":"Asian","desc":"Race distribution"},{"title":"Gender distribution","content":"2,052 males, 1,949 females","desc":"Gender distribution"},{"title":"Age distribution","content":"from children to the elderly","desc":"Age distribution"},{"title":"Collecting environment","content":"including indoor and outdoor scenes (such as supermarket, mall and community, etc.)","desc":"Collecting environment"},{"title":"Data diversity","content":"different ages, different time periods, different cameras, different human body orientations and postures, different collecting scenes","desc":"Data diversity"},{"title":"Device","content":"surveillance cameras, the image resolution is not less 1,920*1,080","desc":"Device"},{"title":"Data format","content":"the image data format is .jpg, the annotation file format is .json","desc":"Data format"},{"title":"Annotation content","content":"human body rectangular bounding boxes","desc":"Annotation content"},{"title":"Accuracy","content":"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%","desc":"Accuracy"}],"datatag":"Different ages,Different time periods,Different cameras,Different human body orientations and postures,Different collecting scenes","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":"","samplePresentation":[],"officialSummary":"This Multi-view Person Tracking Dataset features 4,001 unique individuals captured across both indoor and outdoor environments, including supermarkets, shopping malls, and residential communities, etc.. Each person is recorded by at least seven distinct cameras, providing rich cross-view perspectives. The dataset offers high diversity in age groups, time of day, camera viewpoints, human orientations, and body postures. It is ideal for computer vision tasks such as multi-camera person tracking, cross-view person re-identification (ReID), single object tracking, and multi-view object detection. This dataset is highly suitable for developing and evaluating advanced tracking algorithms in complex real-world scenarios.","dataexampl":null,"datakeyword":["multi-view tracking dataset","multi-camera person tracking","cross-view tracking","person re-identification dataset","object tracking dataset","human tracking dataset","multi-angle surveillance dataset","ReID dataset","cross-camera tracking"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Task Type,Modalities","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"computer","BGimg":"","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"]}
https://www.nexdata.ai/shujutang/static/image/index/datatang_tuxiang_default.webp
[]
Multi-view Person Tracking Dataset – 4,001 Subjects for Re-ID and Computer Vision Tasks
multi-view tracking dataset
multi-camera person tracking
cross-view tracking
person re-identification dataset
object tracking dataset
human tracking dataset
multi-angle surveillance dataset
ReID dataset
cross-camera tracking
This Multi-view Person Tracking Dataset features 4,001 unique individuals captured across both indoor and outdoor environments, including supermarkets, shopping malls, and residential communities, etc.. Each person is recorded by at least seven distinct cameras, providing rich cross-view perspectives. The dataset offers high diversity in age groups, time of day, camera viewpoints, human orientations, and body postures. It is ideal for computer vision tasks such as multi-camera person tracking, cross-view person re-identification (ReID), single object tracking, and multi-view object detection. This dataset is highly suitable for developing and evaluating advanced tracking algorithms in complex real-world scenarios.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
![Specifications]()
Specifications
Data size
4,001 people, about 385-2,779 images per person
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]()
Sample
![Recommended Datasets]()
Recommended Dataset
Tell Us Your Special Needs
19a8746e-13de-4f91-bbbe-691575583f1a
Specifications
Sample
Recommended Dataset
