TY - JOUR
T1 - Automatic Extrinsic Calibration of a Camera and a 2D LiDAR with Point-Line Correspondences
AU - Kim, Jae Yeul
AU - Ha, Jong Eun
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2023
Y1 - 2023
N2 - Extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to fuse information from two sensors by representing the information under the same frame. Various geometric constraints such as point-plane, point-line, and point-point are used for the extrinsic calibration. Usually, these require a manual step, including control points selection for camera calibration and LiDAR points. We propose a new algorithm for automatic extrinsic calibration with point-line correspondences. A calibration structure with two perpendicular planes having a chessboard on both sides is used for the extrinsic calibration. First, we use predefined colors at specific locations on a chessboard to quickly find the origin of the coordinate system. Second, we robustly detect three control points on LiDAR raw data using a geometric constraint that two end points among three control points should lie on the same line. The initial linear solution is obtained by using a point-line constraint. Finally, it is refined by nonlinear minimization, which gives a 15.3% improvement compared to the linear solution. Experimental results show the feasibility of the proposed algorithm.
AB - Extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to fuse information from two sensors by representing the information under the same frame. Various geometric constraints such as point-plane, point-line, and point-point are used for the extrinsic calibration. Usually, these require a manual step, including control points selection for camera calibration and LiDAR points. We propose a new algorithm for automatic extrinsic calibration with point-line correspondences. A calibration structure with two perpendicular planes having a chessboard on both sides is used for the extrinsic calibration. First, we use predefined colors at specific locations on a chessboard to quickly find the origin of the coordinate system. Second, we robustly detect three control points on LiDAR raw data using a geometric constraint that two end points among three control points should lie on the same line. The initial linear solution is obtained by using a point-line constraint. Finally, it is refined by nonlinear minimization, which gives a 15.3% improvement compared to the linear solution. Experimental results show the feasibility of the proposed algorithm.
KW - camera
KW - Extrinsic calibration
KW - LiDAR
KW - sensor fusion
UR - http://www.scopus.com/inward/record.url?scp=85165881871&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2023.3298055
DO - 10.1109/ACCESS.2023.3298055
M3 - Article
AN - SCOPUS:85165881871
SN - 2169-3536
VL - 11
SP - 76904
EP - 76912
JO - IEEE Access
JF - IEEE Access
ER -