Tilt Photography and Lidar Three-Dimensional Scanning for Route Spatial Relationship Detection

Xiaobin Li; Zuhong Liang; Yong Li; Qi Xiao; You Zhou

doi:10.3788/LOP202158.1628003

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 16 >Page 1628003 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 16, 1628003 (2021)

Tilt Photography and Lidar Three-Dimensional Scanning for Route Spatial Relationship Detection

Xiaobin Li^*, Zuhong Liang, Yong Li, Qi Xiao, and You Zhou

Author Affiliations

Jiangmen Power Supply Bureau of Guangdong Power Grid Co., Ltd, Jiangmen, Guangdong 529000, China

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DOI: 10.3788/LOP202158.1628003 Cite this Article Set citation alerts

Xiaobin Li, Zuhong Liang, Yong Li, Qi Xiao, You Zhou. Tilt Photography and Lidar Three-Dimensional Scanning for Route Spatial Relationship Detection[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1628003 Copy Citation Text

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Fig. 1. Flow chart of the data fusion

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Fig. 2. Residual error of the coordinate transformation point

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Fig. 3. Scanning result of the point cloud. (a) Point cloud 1; (b) point cloud 2

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Fig. 4. True 3D model based on tilt photography

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Fig. 5. True 3D model based on laser point cloud and tilt photography

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Fig. 6. Spatial relationship of the route

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Fig. 7. Measured spatial relationship of the route

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No.	Ground truth			Calculated value			Difference value
No.	x	y	h	x	y	h	D_x	D_y	D_h	Difference	Algorithm
D₁	24060.021	37224.324	22.443	24060.020	37224.322	22.444	0.001	0.002	-0.001	0.00240	Bursa
D₁	24060.021	37224.324	22.443	24060.021	37224.323	22.444	-0.0002	0.001	-0.001	0.00143	improved
D₂	24823.904	47866.557	5.833	24823.904	47866.556	5.831	0	0.001	0.002	0.00224	Bursa
D₂	24823.904	47866.557	5.833	24823.904	47866.557	5.832	0	0	0.001	0.00100	improved
D₃	26115.766	56014.570	7.750	26115.768	56014.572	7.752	-0.002	-0.002	-0.002	0.00346	Bursa
D₃	26115.766	56014.570	7.750	26115.767	56014.571	7.751	-0.001	-0.001	-0.001	0.00173	improved
D₄	26349.928	40731.982	3.899	26349.926	40731.983	3.900	0.002	-0.001	-0.001	0.00245	Bursa
D₄	26349.928	40731.982	3.899	26349.928	40731.981	3.900	0	0.001	-0.001	0.00141	improved
D₅	28106.627	28881.954	3.686	28106.626	28881.957	3.685	0.001	-0.003	0.001	0.00332	Bursa
D₅	28106.627	28881.954	3.686	28106.626	28881.952	3.684	0.001	0.002	0.002	0.00300	improved
D₆	29318.775	36961.722	3.580	29318.777	36961.723	3.577	-0.002	-0.001	0.003	0.00343	Bursa
D₆	29318.775	36961.722	3.580	29318.775	36961.720	3.582	0	0.002	-0.002	0.00283	improved

Table 1. Residual table of the improved algorithm unit: m

No.	Calculated value			Surveyed value			Difference value
No.	x	y	h	x	y	h	D_x	D_y	D_h
P₁	32659.71	62922.242	66.616	32659.708	62922.247	66.605	-0.002	0.005	-0.011
P₂	42807.804	64663.308	72.891	42807.799	64663.306	72.869	-0.005	-0.003	-0.022
P₃	44881.183	85990.467	57.705	44881.190	85990.450	57.724	0.007	-0.017	0.019
P₄	49879.346	54628.685	52.897	49879.326	54628.679	52.895	-0.019	-0.006	-0.002
P₅	51569.381	68903.335	55.265	51569.365	68903.343	55.263	-0.016	0.008	-0.002
P₆	52650.06	72017.472	53.668	52650.048	72017.471	53.656	-0.012	0	-0.012
P₇	54060.021	57224.324	72.443	54060.008	57224.310	72.452	-0.013	-0.014	0.009
P₈	56349.928	60731.982	53.899	56349.923	60731.964	53.913	-0.005	-0.018	0.013
P₉	58106.627	48881.954	53.686	58106.630	48881.963	53.685	0.003	0.009	-0.001
P₁₀	59318.775	56961.722	53.580	59318.767	56961.735	53.588	-0.008	0.013	0.008

Table 2. Precision of the field survey unit: m

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