Giovanni Fusco, Ender Tekin, Richard E Ladner, James M Coughlan
{"title":"Using Computer Vision to Access Appliance Displays.","authors":"Giovanni Fusco, Ender Tekin, Richard E Ladner, James M Coughlan","doi":"10.1145/2661334.2661404","DOIUrl":null,"url":null,"abstract":"<p><p>People who are blind or visually impaired face difficulties accessing a growing array of everyday appliances, needed to perform a variety of daily activities, because they are equipped with electronic displays. We are developing a \"Display Reader\" smartphone app, which uses computer vision to help a user acquire a usable image of a display, to address this problem. The current prototype analyzes video from the smartphone's camera, providing real-time feedback to guide the user until a satisfactory image is acquired, based on automatic estimates of image blur and glare. Formative studies were conducted with several blind and visually impaired participants, whose feedback is guiding the development of the user interface. The prototype software has been released as a Free and Open Source (FOSS) project.</p>","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2014 ","pages":"281-282"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2661334.2661404","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASSETS. Annual ACM Conference on Assistive Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2661334.2661404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
People who are blind or visually impaired face difficulties accessing a growing array of everyday appliances, needed to perform a variety of daily activities, because they are equipped with electronic displays. We are developing a "Display Reader" smartphone app, which uses computer vision to help a user acquire a usable image of a display, to address this problem. The current prototype analyzes video from the smartphone's camera, providing real-time feedback to guide the user until a satisfactory image is acquired, based on automatic estimates of image blur and glare. Formative studies were conducted with several blind and visually impaired participants, whose feedback is guiding the development of the user interface. The prototype software has been released as a Free and Open Source (FOSS) project.