Volodymyr Ivanchenko, James Coughlan, Huiying Shen
{"title":"Detecting and Locating Crosswalks using a Camera Phone.","authors":"Volodymyr Ivanchenko, James Coughlan, Huiying Shen","doi":"10.1109/CVPRW.2008.4563143","DOIUrl":null,"url":null,"abstract":"<p><p>Urban intersections are the most dangerous parts of a blind or visually impaired person's travel. To address this problem, this paper describes the novel \"Crosswatch\" system, which uses computer vision to provide information about the location and orientation of crosswalks to a blind or visually impaired pedestrian holding a camera cell phone. A prototype of the system runs on an off-the-shelf Nokia N95 camera phone in real time, which automatically takes a few images per second, analyzes each image in a fraction of a second and sounds an audio tone when it detects a crosswalk. Real-time performance on the cell phone, whose computational resources are limited compared to the type of desktop platform usually used in computer vision, is made possible by coding in Symbian C++. Tests with blind subjects demonstrate the feasibility of the system.</p>","PeriodicalId":74560,"journal":{"name":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":" ","pages":"4563143"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CVPRW.2008.4563143","citationCount":"71","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2008.4563143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 71
Abstract
Urban intersections are the most dangerous parts of a blind or visually impaired person's travel. To address this problem, this paper describes the novel "Crosswatch" system, which uses computer vision to provide information about the location and orientation of crosswalks to a blind or visually impaired pedestrian holding a camera cell phone. A prototype of the system runs on an off-the-shelf Nokia N95 camera phone in real time, which automatically takes a few images per second, analyzes each image in a fraction of a second and sounds an audio tone when it detects a crosswalk. Real-time performance on the cell phone, whose computational resources are limited compared to the type of desktop platform usually used in computer vision, is made possible by coding in Symbian C++. Tests with blind subjects demonstrate the feasibility of the system.