Duan Chi, Wang Zhi, Hao Luo, Fengfa Li, Lianzhong Sun
{"title":"Embedded AI system for interactive vision screen based on human action recognition.","authors":"Duan Chi, Wang Zhi, Hao Luo, Fengfa Li, Lianzhong Sun","doi":"10.1063/5.0076398","DOIUrl":null,"url":null,"abstract":"In recent years, vision screening has emerged globally for employment (on a yearly basis) within primary and high schools since myopia heavily affects school-aged children. However, this is a laborious and time-consuming task. This article proposes an intelligent system for \"self-service\" vision screening. Individuals can accomplish this task independently-without any assistance by technical staff. The technical solution involved within this platform is human action recognition realized by pose estimation (real-time human joint localization in images, including detection, association, and tracking). The developed system is based on a compact and embedded artificial intelligence platform, aided by a red-green-blue-D sensor for ranging and pose extraction. A set of intuitive upper-limb actions was designed for unambiguous recognition and interaction. The deployment of this intelligent system brings great convenience for large-scale and rapid vision screening. Implementation details were extensively described, and the experimental results demonstrated efficiency for the proposed technique.","PeriodicalId":54761,"journal":{"name":"Journal of the Optical Society of America and Review of Scientific Instruments","volume":"29 1","pages":"054104"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Optical Society of America and Review of Scientific Instruments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/5.0076398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In recent years, vision screening has emerged globally for employment (on a yearly basis) within primary and high schools since myopia heavily affects school-aged children. However, this is a laborious and time-consuming task. This article proposes an intelligent system for "self-service" vision screening. Individuals can accomplish this task independently-without any assistance by technical staff. The technical solution involved within this platform is human action recognition realized by pose estimation (real-time human joint localization in images, including detection, association, and tracking). The developed system is based on a compact and embedded artificial intelligence platform, aided by a red-green-blue-D sensor for ranging and pose extraction. A set of intuitive upper-limb actions was designed for unambiguous recognition and interaction. The deployment of this intelligent system brings great convenience for large-scale and rapid vision screening. Implementation details were extensively described, and the experimental results demonstrated efficiency for the proposed technique.