[{"@type":"PropertyValue","name":"Data size","value":"314,178 images, 18 gestures"},{"@type":"PropertyValue","name":"Population distribution","value":"the race distribution is yellow race, the gender distribution is male and female, the age distribution is mainly young and middle-aged"},{"@type":"PropertyValue","name":"Collection environment","value":"indoor scenes and outdoor scenes (natural scenery, roadside street view, square, etc.)"},{"@type":"PropertyValue","name":"Data diversity","value":"multiple scenes, 18 gestures, 5 shooting angels, multiple ages, multiple light conditions"},{"@type":"PropertyValue","name":"Collection device","value":"cellphone"},{"@type":"PropertyValue","name":"Image parameter","value":"the image format is .jpg, the annotated file format is .json"},{"@type":"PropertyValue","name":"Annotation content","value":"21 landmarks annotation (each landmark includes the attribute of visible and visible), gesture type annotation, gesture attributes annotation"},{"@type":"PropertyValue","name":"Accuracy","value":"the accuracy of gesture landmarks annotation is not less than 95%; the accuracies of gesture type and gesture attributes are not less than 95%"}]
{"id":957,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY181130001.png?Expires=2007353651&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=gylX81oruNkv7zt2BSLVCXS749A%3D","type1":"147","type1str":null,"type2":"147","type2str":null,"dataname":"314,178 Images 18_Gestures Recognition Data","datazy":[{"title":"Data size","value":"314,178 images, 18 gestures"},{"title":"Population distribution","value":"the race distribution is yellow race, the gender distribution is male and female, the age distribution is mainly young and middle-aged"},{"title":"Collection environment","value":"indoor scenes and outdoor scenes (natural scenery, roadside street view, square, etc.)"},{"title":"Data diversity","value":"multiple scenes, 18 gestures, 5 shooting angels, multiple ages, multiple light conditions"},{"title":"Collection device","value":"cellphone"},{"title":"Image parameter","value":"the image format is .jpg, the annotated file format is .json"},{"title":"Annotation content","value":"21 landmarks annotation (each landmark includes the attribute of visible and visible), gesture type annotation, gesture attributes annotation"},{"title":"Accuracy","value":"the accuracy of gesture landmarks annotation is not less than 95%; the accuracies of gesture type and gesture attributes are not less than 95%"}],"datatag":"Multiple scenes,18 gestures,21 landmarks annotation,5 shooting angels,Multiple ages,Multiple light conditions","technologydoc":null,"downurl":null,"datainfo":"314,178 18_ Gestures Recognition Data. It includes entertainment gestures and number gestures, total 18 categories.Each gesture covers left and right hand, forehand and backhand, angle rotation etc. This data can be applied to gesture recognition, man-machine interaction, and live broadcasting interaction etc.","standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":["Chinese","gesture attributes annotation","21 gestural landmarks annotation"],"samplePresentation":[["jpg","https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/2.jpg?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=0RNGyxfdqE6W9%2B01Kr3UZjHQFN8%3D","/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/2.jpg",""],["jpg","https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/3.jpg?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=gI%2B%2Fwj5n9VCkjN883pzXcNx5qPA%3D","/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/3.jpg",""],["jpg","https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/1.jpg?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=DalaJQsiijBJUNuCTU2LwcckTvs%3D","/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/1.jpg",""]],"officialSummary":"314,178 Images 18_Gestures Recognition Data. This data diversity includes multiple scenes, 18 gestures, 5 shooting angels, multiple ages and multiple light conditions. For annotation, gesture 21 landmarks (each landmark includes the attribute of visible and visible), gesture type and gesture attributes were annotated. This data can be used for tasks such as gesture recognition and human-machine interaction.","dataexampl":"","datakeyword":["multiple scenes"," 18 gestures"," 5 shooting angels"," multiple ages"," multiple light conditions"," gesture recognition"," 21 gestural landmarks annotation"],"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":"no","firstList":[["jpg","https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/5.jpg?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=KlIRyDA1YHgGZbsUYcxgLqizc6c%3D","/data/apps/damp/temp/ziptemp/APY181130001_demo1712829638577/APY181130001_demo/5.jpg",""]]}
314,178 Images 18_Gestures Recognition Data. This data diversity includes multiple scenes, 18 gestures, 5 shooting angels, multiple ages and multiple light conditions. For annotation, gesture 21 landmarks (each landmark includes the attribute of visible and visible), gesture type and gesture attributes were annotated. This data can be used for tasks such as gesture recognition and human-machine interaction.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
314,178 images, 18 gestures
Population distribution
the race distribution is yellow race, the gender distribution is male and female, the age distribution is mainly young and middle-aged
Collection environment
indoor scenes and outdoor scenes (natural scenery, roadside street view, square, etc.)
the image format is .jpg, the annotated file format is .json
Annotation content
21 landmarks annotation (each landmark includes the attribute of visible and visible), gesture type annotation, gesture attributes annotation
Accuracy
the accuracy of gesture landmarks annotation is not less than 95%; the accuracies of gesture type and gesture attributes are not less than 95%
Sample
Recommended Dataset
116,048 Sets - 3D Handpose Dataset
This dataset contains 116,048 sets of 3D handpose data, each set includes hand mask image(RGB, 24-bit), depth image(16-bit), camera intrinsic parameter file(TXT), 3D keypoints file(OBJ), mesh file(OBJ), gesture type file(TXT), keypoints demo image(JPG), and mesh demo image(JPG). The data is collected indoors, with the right hand (no handheld objects), covering both first-person and third-person perspectives, multiple gesture types, finger poses, hand overall rotation poses, individuals and Kinect devices used. This dataset does not include personally identifiable facial information, with hand mask images and depth images aligned. This dataset can be used for tasks such as handpose recognition, hand 3D reconstruction, and hand keypoints detection.
2,341 People Gesture Recognition Data in Online Conference Scenes
2,341 People Gesture Recognition Data in Meeting Scenes includes Asians, Caucasians, blacks, and browns, and the age is mainly young and middle-aged. It collects a variety of indoor office scenes, covering meeting rooms, coffee shops, libraries, bedrooms, etc. Each person collected 18 pictures and 2 videos. The pictures included 18 gestures such as clenching a fist with one hand and heart-to-heart with one hand, and the video included gestures such as clapping.
Human behavior data Gesture recognition data set Conference scene Human behavior data collection
180,717 Images - Sign Language Gestures Recognition Data
180,717 Images - Sign Language Gestures Recognition Data. The data diversity includes multiple scenes, 41 static gestures, 95 dynamic gestures, multiple photographic angles, and multiple light conditions. In terms of data annotation, 21 landmarks, gesture types, and gesture attributes were annotated. This dataset can be used for tasks such as gesture recognition and sign language translation.
Sign language gesturesmultiple scenes static gestures dynamic gestures multiple photographic angles multiple light conditions21 landmarks gesture type gesture attributes
558,870 Videos - 50 Types of Dynamic Gesture Recognition Data
558,870 Videos - 50 Types of Dynamic Gesture Recognition Data. The collecting scenes of this dataset include indoor scenes and outdoor scenes (natural scenery, street view, square, etc.). The data covers males and females. The age distribution ranges from teenager to senior. The data diversity includes multiple scenes, 50 types of dynamic gestures, 5 photographic angles, multiple light conditions, different photographic distances. This data can be used for dynamic gesture recognition of smart homes, audio equipments and on-board systems.
Vehicle dynamic gesture data home gesture data gesture recognition data 21 key point gesture image data static gesture data dynamic gesture data key point dataset key point annotation gesture key point dataset