{"title":"AI Body Detection and Teaching System based on Mediapipe Machine Learning Platform and OpenCV Computer Vision Library","authors":"Ling Li, Huijuan Huang, Shaogeng Zeng, Huiqi Cao, Rongrui Zheng, Shuimei Lin","doi":"10.18282/l-e.v10i8.3115","DOIUrl":null,"url":null,"abstract":"To solve the problems of low intera ctivity, high cost, large amount of data, “difficult to quantify, difficult to record, \ndifficult to supervise, difficult to analyze” of human motion detection correction devices on the market today, we designed an \nintelligent device based on Mediapipe machine learning platform and OpenCV computer based on Raspberry Pi, camera and display. \nWe designed an intelligent device for AI body detection and teaching based on Mediapipe machine learning platform and OpenCV \ncomputer vision library. By combining chip, sensor, computing platform and technology level of computer vision, speech recognition \nand machine learning, the device can capture human movement in real time by using camera equipment, judge the accuracy and \ncompleteness of user’s movement according to the comparison of standard movement, and give feedback to the user in real time by \nvoice broadcast and image prompt. The test results show that the device has the advantages of low cost, simple structure, intelligence, \nunmanned, data and accuracy, which provides a feasible solution to further enhance the convenience and accuracy of unmanned \nmovement teaching and rehabilitation training.","PeriodicalId":199440,"journal":{"name":"Learning & Education","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18282/l-e.v10i8.3115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To solve the problems of low intera ctivity, high cost, large amount of data, “difficult to quantify, difficult to record,
difficult to supervise, difficult to analyze” of human motion detection correction devices on the market today, we designed an
intelligent device based on Mediapipe machine learning platform and OpenCV computer based on Raspberry Pi, camera and display.
We designed an intelligent device for AI body detection and teaching based on Mediapipe machine learning platform and OpenCV
computer vision library. By combining chip, sensor, computing platform and technology level of computer vision, speech recognition
and machine learning, the device can capture human movement in real time by using camera equipment, judge the accuracy and
completeness of user’s movement according to the comparison of standard movement, and give feedback to the user in real time by
voice broadcast and image prompt. The test results show that the device has the advantages of low cost, simple structure, intelligence,
unmanned, data and accuracy, which provides a feasible solution to further enhance the convenience and accuracy of unmanned
movement teaching and rehabilitation training.