[{"@type":"PropertyValue","name":"Data size","value":"2,769 people, 1-25 cameras for each person"},{"@type":"PropertyValue","name":"Population distribution","value":"race distribution: 2,646 Caucasians, 47 Asians, 76 blacks; gender distribution: 1,091 males, 1,678 females; age distribution: mainly young and middle-aged"},{"@type":"PropertyValue","name":"Collecting environment","value":"department store"},{"@type":"PropertyValue","name":"Data diversity","value":"different age groups, different time periods, different cameras, different human body orientations and postures"},{"@type":"PropertyValue","name":"Device","value":"surveillance cameras, the resolution includes 960*576 and 1,440*1,616"},{"@type":"PropertyValue","name":"Collecting angle","value":"looking down angle"},{"@type":"PropertyValue","name":"Collecting time","value":"10:00-20:00"},{"@type":"PropertyValue","name":"Data format","value":"the image data format is .jpg or png, the annotation file format is .json"},{"@type":"PropertyValue","name":"Annotation content","value":"human body rectangular bounding boxes, 15 human body attributes"},{"@type":"PropertyValue","name":"Accuracy rate","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%; annotation accuracy of human attributes is over 97%; the accuracy of label annotation is not less than 97%"}]
{"id":1322,"datatype":"1","titleimg":"/shujutang/static/image/index/datatang_tuxiang_default.webp","type1":"147","type1str":null,"type2":"147","type2str":null,"dataname":"2,769 People - CCTV Re-ID Data in Europe","datazy":[{"title":"Data size","value":"2,769 people, 1-25 cameras for each person"},{"title":"Population distribution","value":"race distribution: 2,646 Caucasians, 47 Asians, 76 blacks; gender distribution: 1,091 males, 1,678 females; age distribution: mainly young and middle-aged"},{"title":"Collecting environment","value":"department store"},{"title":"Data diversity","value":"different age groups, different time periods, different cameras, different human body orientations and postures"},{"title":"Device","value":"surveillance cameras, the resolution includes 960*576 and 1,440*1,616"},{"title":"Collecting angle","value":"looking down angle"},{"title":"Collecting time","value":"10:00-20:00"},{"title":"Data format","value":"the image data format is .jpg or png, the annotation file format is .json"},{"title":"Annotation content","value":"human body rectangular bounding boxes, 15 human body attributes"},{"title":"Accuracy rate","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%; annotation accuracy of human attributes is over 97%; the accuracy of label annotation is not less than 97%"}],"datatag":"Different age groups,Different time periods,Different cameras,Different human body orientations and postures","technologydoc":null,"downurl":null,"datainfo":"","standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":"","samplePresentation":["mp4",""],"officialSummary":"2,769 People – CCTV Re-ID Data in Europe. The data includes males and females, the race distribution is Caucasian, black, Asian, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different cameras, different human body orientations and postures. 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.","dataexampl":"","datakeyword":["European","CCTV","Re-ID","different age groups"," different time periods"," different cameras"," different human body orientations and postures","the human body rectangular bounding boxes","the rectangular bounding boxes"],"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"],"single":"yes"}
2,769 People – CCTV Re-ID Data in Europe. The data includes males and females, the race distribution is Caucasian, black, Asian, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different cameras, different human body orientations and postures. 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.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
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%
Specifications
Sample
Recommended Dataset
