{"title":"Bundle adjustment using single-track vehicle model","authors":"Jonas Nilsson, J. Fredriksson, A. Ödblom","doi":"10.1109/ICRA.2013.6630977","DOIUrl":null,"url":null,"abstract":"This paper describes a method for estimating the 6-DoF viewing parameters of a calibrated vehicle-mounted camera. Visual features are combined with standard in-vehicle sensors and a single-track vehicle motion model in a bundle adjustment framework to produce a jointly optimal viewing parameter estimate. Results show that the vehicle motion model in combination with in-vehicle sensors exhibit good accuracy in estimating planar vehicle motion. This property is preserved, when combining these information sources with vision. Furthermore, the accuracy obtained from vision-only in direction estimation is not only maintained, but in fact further improved, primarily in situations where the matched visual features are few.","PeriodicalId":259746,"journal":{"name":"2013 IEEE International Conference on Robotics and Automation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA.2013.6630977","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
This paper describes a method for estimating the 6-DoF viewing parameters of a calibrated vehicle-mounted camera. Visual features are combined with standard in-vehicle sensors and a single-track vehicle motion model in a bundle adjustment framework to produce a jointly optimal viewing parameter estimate. Results show that the vehicle motion model in combination with in-vehicle sensors exhibit good accuracy in estimating planar vehicle motion. This property is preserved, when combining these information sources with vision. Furthermore, the accuracy obtained from vision-only in direction estimation is not only maintained, but in fact further improved, primarily in situations where the matched visual features are few.