{"title":"Real-Time Multiple Vehicles Tracking with Occlusion Handling","authors":"Wei Fang, Yong Zhao, Yule Yuan, Kai Liu","doi":"10.1109/ICIG.2011.140","DOIUrl":null,"url":null,"abstract":"Vehicle detection and tracking is fundamental to vision-based traffic applications. We introduce a real-time system for multiple vehicles tracking with occlusion handling. Firstly, a method of three-level noise removing and vehicle segmentation is presented. Then the segmented vehicles are tracked by using an approach based on normalized area of intersection and the system keeps tracking the occluded vehicles independently by local corner features matching and tracking. Experimental results from video sequences of real-world traffic scenes in the daytime are presented which demonstrate the effectiveness of the algorithm.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Image and Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIG.2011.140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Vehicle detection and tracking is fundamental to vision-based traffic applications. We introduce a real-time system for multiple vehicles tracking with occlusion handling. Firstly, a method of three-level noise removing and vehicle segmentation is presented. Then the segmented vehicles are tracked by using an approach based on normalized area of intersection and the system keeps tracking the occluded vehicles independently by local corner features matching and tracking. Experimental results from video sequences of real-world traffic scenes in the daytime are presented which demonstrate the effectiveness of the algorithm.