中国邮电高校学报(英文) ›› 2020, Vol. 27 ›› Issue (4): 91-98.doi: 10.19682/j.cnki.1005-8885.2020.0040

• Others • 上一篇    

Monocular camera and 3D lidar joint calibration

郑鑫 吴晓军   

  1. 西安交通大学
  • 收稿日期:2019-03-01 修回日期:2020-08-18 出版日期:2020-08-31 发布日期:2020-08-31
  • 通讯作者: 郑鑫 E-mail:396848385@qq.com

Monocular camera and 3D lidar joint calibration

Zheng Xin, Wu Xiaojun   


  • Received:2019-03-01 Revised:2020-08-18 Online:2020-08-31 Published:2020-08-31
  • Contact: Zheng Xin E-mail:396848385@qq.com

摘要: Joint calibration of sensors is an important prerequisite in intelligent driving scene retrieval and recognition. A simple and efficient solution is proposed for solving the problem of automatic joint calibration registration between the monocular camera and the 16-line lidar. The study is divided into two parts: single-sensor independent calibration and multi-sensor joint registration, in which the selected objective world is used. The system associates the lidar coordinates with the camera coordinates. The lidar and the camera are used to obtain the normal vectors of the calibration plate and the point cloud data representing the calibration plate by the appropriate algorithm. Iterated closest points (ICP) is the method used for the iterative refinement of the registration.

关键词:

calibration registration| monocular camera| 16-line lidar| multi-sensor, ICP

Abstract: Joint calibration of sensors is an important prerequisite in intelligent driving scene retrieval and recognition. A simple and efficient solution is proposed for solving the problem of automatic joint calibration registration between the monocular camera and the 16-line lidar. The study is divided into two parts: single-sensor independent calibration and multi-sensor joint registration, in which the selected objective world is used. The system associates the lidar coordinates with the camera coordinates. The lidar and the camera are used to obtain the normal vectors of the calibration plate and the point cloud data representing the calibration plate by the appropriate algorithm. Iterated closest points (ICP) is the method used for the iterative refinement of the registration.

Key words: calibration registration|monocular camera|16-line lidar| multi-sensor, ICP