Mingyu Gao, Qingfeng Jiang, Da Xu, Yi Chen, Junfan Wang, Huipin Lin
{"title":"Design and Implementation of a Dual-Modal Ranging System Using Joint Calibration method","authors":"Mingyu Gao, Qingfeng Jiang, Da Xu, Yi Chen, Junfan Wang, Huipin Lin","doi":"10.1145/3577117.3577119","DOIUrl":null,"url":null,"abstract":"With the bottleneck of traffic image ranging and the development of LiDAR, which collected by LiDAR, point cloud has received more and more attention as a supplement to image data. In order to achieve accurate ranging with the help of point cloud data, this paper implements a vehicle distance detection system based on the camera and LiDAR with the help of PCL and ROS, using the semantic information of the camera and the distance information of the LiDAR. The test shows that the system can detect the vehicle distance more accurately, and can also be further applied to other intelligent traffic scenarios.","PeriodicalId":309874,"journal":{"name":"Proceedings of the 6th International Conference on Advances in Image Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Advances in Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3577117.3577119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the bottleneck of traffic image ranging and the development of LiDAR, which collected by LiDAR, point cloud has received more and more attention as a supplement to image data. In order to achieve accurate ranging with the help of point cloud data, this paper implements a vehicle distance detection system based on the camera and LiDAR with the help of PCL and ROS, using the semantic information of the camera and the distance information of the LiDAR. The test shows that the system can detect the vehicle distance more accurately, and can also be further applied to other intelligent traffic scenarios.