[{"@type":"PropertyValue","name":"Data size","value":"212 people, there are 11 cameras, 48,000 images"},{"@type":"PropertyValue","name":"Population distribution","value":"the race distribution is Asian, the gender distribution is male and female, the age distribution is from children to the elderly"},{"@type":"PropertyValue","name":"Collecting environment","value":"indoor scenes"},{"@type":"PropertyValue","name":"Data diversity","value":"different ages, different cameras, different human body orientations and postures"},{"@type":"PropertyValue","name":"Device","value":"surveillance cameras, the image resolution is 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 5 pixels, and the qualified rate of the bounding boxes shall not be lower than 95%; Annotation accuracy of ID is over 95%"}]
{"id":1191,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY220817001.png?Expires=2007353711&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=OGujFhzluU139HHaJgxG2YZQVyE%3D","type1":"147","type1str":null,"type2":"148","type2str":null,"dataname":"212 Person Indoor Surveillance Tracking Dataset – 48K Images for Object Tracking & Human Detection","datazy":[{"title":"Data size","desc":"Data size","content":"212 people, there are 11 cameras, 48,000 images"},{"title":"Population distribution","desc":"Population distribution","content":"the race distribution is Asian, the gender distribution is male and female, the age distribution is from children to the elderly"},{"title":"Collecting environment","desc":"Collecting environment","content":"indoor scenes"},{"title":"Data diversity","desc":"Data diversity","content":"different ages, different cameras, different human body orientations and postures"},{"title":"Device","desc":"Device","content":"surveillance cameras, the image resolution is 1,920*1,080"},{"title":"Data format","desc":"Data format","content":"the image data format is .jpg, the annotation file format is .json"},{"title":"Annotation content","desc":"Annotation content","content":"human body rectangular bounding boxes"},{"title":"Accuracy","desc":"Accuracy","content":"A rectangular bounding box of human body is qualified when the deviation is not more than 5 pixels, and the qualified rate of the bounding boxes shall not be lower than 95%; Annotation accuracy of ID is over 95%"}],"datatag":"Different ages,Different cameras,Different human body orientations and postures","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":"212 Person Indoor Surveillance Tracking Dataset – 48K Images for Object Tracking & Human Detection. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different shooting angles, different human body orientations and postures. For annotation, we adpoted rectangular bounding boxes annotations on human body. This dataset can be used for multiple object tracking and other tasks.","dataexampl":null,"datakeyword":["multi-person tracking dataset","human tracking data","object tracking dataset","diverse age tracking","bounding box annotations","multi-view tracking data","human detection dataset","AI tracking dataset","pedestrian tracking dataset"],"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"]}
212 Person Indoor Surveillance Tracking Dataset – 48K Images for Object Tracking & Human Detection
multi-person tracking dataset
human tracking data
object tracking dataset
diverse age tracking
bounding box annotations
multi-view tracking data
human detection dataset
AI tracking dataset
pedestrian tracking dataset
212 Person Indoor Surveillance Tracking Dataset – 48K Images for Object Tracking & Human Detection. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different shooting angles, different human body orientations and postures. For annotation, we adpoted rectangular bounding boxes annotations on human body. This dataset can be used for multiple object tracking 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
212 people, there are 11 cameras, 48,000 images
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
indoor scenes
Data diversity
different ages, different cameras, different human body orientations and postures
Device
surveillance cameras, the image resolution is 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 5 pixels, and the qualified rate of the bounding boxes shall not be lower than 95%; Annotation accuracy of ID is over 95%
Specifications
Sample
Recommended Dataset
