{"title":"A system architecture for real time traffic monitoring in foggy video","authors":"Sangkyoon Kim, Soonyoung Park, Kyoungho Choi","doi":"10.1109/FCV.2015.7103720","DOIUrl":null,"url":null,"abstract":"In foggy video, the visibility and contrast of objects are decreased dramatically, which causes the performance degradation of traffic monitoring systems. In this paper, an architecture for real-time traffic monitoring system is presented for foggy video. For the real-time traffic monitoring, it is required to satisfy two major constraints. First, the quality of an image after fog removal is good enough for further processing such as object detection and tracking. Second, it has to be computationally cheap for real-time processing. In this paper, a parallel architecture is proposed, consisting of N threads, for a real-time traffic monitoring system. The proposed parallel architecture shows the significant reduction of processing time for the development of real-time traffic monitoring systems.","PeriodicalId":424974,"journal":{"name":"2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCV.2015.7103720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In foggy video, the visibility and contrast of objects are decreased dramatically, which causes the performance degradation of traffic monitoring systems. In this paper, an architecture for real-time traffic monitoring system is presented for foggy video. For the real-time traffic monitoring, it is required to satisfy two major constraints. First, the quality of an image after fog removal is good enough for further processing such as object detection and tracking. Second, it has to be computationally cheap for real-time processing. In this paper, a parallel architecture is proposed, consisting of N threads, for a real-time traffic monitoring system. The proposed parallel architecture shows the significant reduction of processing time for the development of real-time traffic monitoring systems.