Table 1.

This table summarizes the previous works for LiDAR and camera calibration. Their strengths and weaknesses are also included.

	Automatic	# of Observations	Calibration Object	Strength	Weakness
Rodrigues et al. [1]	no	6	planar with circular hole	low noise ratio by texture	no guarantee for convergence
Alismail et al. [4]	yes	1	black planar circle	automatic	the center of the circle must be marked
Park et al. [7]	no	3	white homogeneous, planar	no additional LiDAR noise by texture	estimated board edges
Gong et al. [8]	no	2	arbitrary trihedron	orthogonality of the object is not required	much human intervention
Velas et al. [9]	yes	1	planar with holes, white background	automatic	difficult calibration setup
Geiger et al. [11]	yes	1	planar, chessboards	only one shot is needed by sensors	multiple chessboards are needed
Hassanein et al. [12]	yes	1	well-textured trihedron	automatic	camera system must be pre-calibrated