Intrinsic and Extrinsic Calibration of Roadside LiDAR and Camera

X Jing, F Han,X Ding, Y Wang,R Xiong

2022 China Automation Congress (CAC)(2022)

引用 0|浏览2
暂无评分
摘要
LiDAR-camera intrinsic and extrinsic parameters calibration is a prerequisite for LiDAR-camera sensor suite in the cooperative vehicle-infrastructure system or autonomous driving system. However, the calibration of LiDAR-camera is not trivial in some special scenes such as traffic scenes since the traditional target-based calibration methods are subject to the road condition. Moreover, the changing intrinsic parameters of the camera owing to focusing also pose unique challenges to such calibration tasks. Hence, a novel targetless method that jointly performs the intrinsic and extrinsic parameters calibration of LiDAR and camera sensor suite is proposed in this paper. The 2D and 3D features are collected from color images and point cloud respectively. The distance transform image is obtained from a 2D feature map and used as a reprojection error energy function for optimization. Alternatively, the observability of intrinsic and extrinsic parameters in our calibration system is theoretically verified, and the proposed method is tested in simulation and real-world scenes. Experiment results show that the method has better robustness and accuracy than other targetless calibration methods.
更多
查看译文
关键词
2D feature map,3D features,autonomous driving system,calibration system,calibration tasks,camera sensor suite,color images,cooperative vehicle-infrastructure system,distance transform image,extrinsic parameters calibration,intrinsic parameters calibration,LiDAR-camera sensor suite,point cloud,real-world scenes,reprojection error energy function,road condition,roadside LiDAR,target-based calibration methods,targetless calibration methods,traffic scenes,vehicle-infrastructure system
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要