Calibration Method of 2D LIDAR and Camera Based on Indoor Structural Features

S/N	x/m	y/m	a	b	c
1	-0.645 679 53	0.025 819 36	-275	172	83 874
2	-0.663 591 86	-0.157 623 35	-269	219	32 780
3	-0.643 988 79	-0.256 961 64	-307	131	22 593
4	-0.892 779 23	-0.220 791 22	-423	244	56 064
5	-0.919 356 82	-0.116 384 39	-381	177	82 758
6	-0.930 696 01	0.445 599 08	-357	-268	260 015
7	-1.013 609 30	0.073 209 52	-474	-182	210 346
8	-0.919 355 99	-0.183 984 88	-189	-133	62 447
9	-1.143 314 60	-0.059 158 44	-330	-183	132 366
10	-1.206 768 00	0.121 189 59	-346	-359	193 661
11	-1.210 898 40	0.296 762 59	-477	-243	269 037
12	-1.266 390 80	-0.534 483 91	-258	-99	45 486

Table 2. Reprojection errors before optimization
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Table 2. Reprojection errors before optimization
S/N 1 2 3 4 5 6
error 0.572 4 0.049 9 0.426 9 0.848 8 1.423 1 0.117 6
S/N 7 8 9 10 11 12
error 0.196 3 0.274 4 0.186 7 0.196 9 0.108 5 0.104 3

Table 3. Matrices of different calibration methods

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Table 3. Matrices of different calibration methods

Method	Matrix
Optimized method	$[\begin{matrix} 0.877 757 & - 0.999 888 & 0.331 104 \\ 0.479 099 & 0.014 996 & 0.943 594 \\ 0.002 499 & 9.205 273 \times 10^{- 5} & 8.637 213 \times 10^{- 4} \end{matrix}]$
Ref. [19]	$[\begin{matrix} 0.878 759 5 & - 0.999 820 & 0.330 258 \\ 0.477 258 2 & 0.018 967 & 0.943 890 \\ 0.002 501 3 & 9.043 625 \times 10^{- 5} & 8.697 315 \times 10^{- 4} \end{matrix}]$

Table 4. Reprojection error comparison
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Table 4. Reprojection error comparison
S/N 1 2 3 4 5
This work 0.025 9 0.078 8 0.052 8 0.017 8 0.054 3
Ref. [19] 0.572 4 0.049 9 0.426 9 0.117 6 0.196 3
S/N 6 7 8 9 10
This work 0.090 5 0.087 5 0.021 5 0.004 5 0.025 7
Ref. [19] 0.274 4 0.186 7 0.196 9 0.108 5 0.104 3

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Lei ZHANG, Xiao-bin XU, Jia HE, Kai-yua ZHU, Min-zhou LUO, Zhi-ying TAN. Calibration Method of 2D LIDAR and Camera Based on Indoor Structural Features[J]. Acta Photonica Sinica, 2020, 49(12): 61

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