S. Mohottala, Shintaro Ono, M. Kagesawa, K. Ikeuchi
{"title":"Fusion of a camera and a laser range sensor for vehicle recognition","authors":"S. Mohottala, Shintaro Ono, M. Kagesawa, K. Ikeuchi","doi":"10.1109/CVPRW.2009.5204099","DOIUrl":null,"url":null,"abstract":"This paper presents a system that fuses data from a vision sensor and a laser sensor for detection and classification. Fusion of a vision sensor and a laser range sensor enables us to obtain 3D information of an object together with its textures, offering high reliability and robustness to outdoor conditions. To evaluate the performance of the system, it is applied to recognition of on-street parked vehicles scanned from a moving probe vehicle. The evaluation experiments show obviously successful results, with a detection rate of 100% and an accuracy over 95% in recognizing four vehicle classes.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2009.5204099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper presents a system that fuses data from a vision sensor and a laser sensor for detection and classification. Fusion of a vision sensor and a laser range sensor enables us to obtain 3D information of an object together with its textures, offering high reliability and robustness to outdoor conditions. To evaluate the performance of the system, it is applied to recognition of on-street parked vehicles scanned from a moving probe vehicle. The evaluation experiments show obviously successful results, with a detection rate of 100% and an accuracy over 95% in recognizing four vehicle classes.