{"title":"An automated method for understanding road traffic signs in a video scene captured by a mobile camera","authors":"T. Uchida, H. Hanaizumi","doi":"10.1109/ICIT.2012.6209922","DOIUrl":null,"url":null,"abstract":"We have already proposed a method for detecting road traffic signs in a video scene. In order to realize flexible detection in shape deformation due to discrepancy between target position and camera direction, multiple template techniques were introduced. Here, we proposed an automated method for understanding road traffic signs in a video scene. The method was located at the 2nd process for understanding the signs detected by the previous method. The sign understanding process was reduced to evaluation of both spatial and spectral similarities among the sign templates with possible deformations and signs detected. A binary decision tree classifier was introduced for efficient performing the evaluations.","PeriodicalId":365141,"journal":{"name":"2012 IEEE International Conference on Industrial Technology","volume":"367 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Industrial Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2012.6209922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
We have already proposed a method for detecting road traffic signs in a video scene. In order to realize flexible detection in shape deformation due to discrepancy between target position and camera direction, multiple template techniques were introduced. Here, we proposed an automated method for understanding road traffic signs in a video scene. The method was located at the 2nd process for understanding the signs detected by the previous method. The sign understanding process was reduced to evaluation of both spatial and spectral similarities among the sign templates with possible deformations and signs detected. A binary decision tree classifier was introduced for efficient performing the evaluations.