Optimization of 3D reconstruction method for urban cable tunnel based on SfM method

doi:10.11996/JG.j.2095-302X.2023030540

Abstract

Abstract:

The three-dimensional reconstruction technology is extensively applied to various scenarios such as urban subway tunnels and railway tunnels to visualize tunnel structure and analyze tunnel properties. For urban cable tunnels, due to many internal obstacles with smaller sections than subway tunnels, there are some difficulties in using the traditional three-dimensional reconstruction methods such as 3D laser scanners. Photogrammetry technology, with its portable equipment, holds significant potential in the three-dimensional reconstruction of cable tunnels. Based on photogrammetry theory, this paper summarized and analyzed various factors affecting the effect of 3D reconstruction of cable tunnels and established a model evaluation method for 3D reconstruction of cable tunnel scenes. Experiments were carried out in a gas insulated transmission line (GIL) cable tunnel in Nantong, Jiangsu Province. To mitigate the problem of uneven brightness and darkness in the original image, histogram equalization and gamma transform were employed for enhanced preprocessing, thereby restoring the lining details of the dark part of the tunnel image. Based on the structure from motion (SfM) 3D reconstruction method, a 3D model of the cable tunnel with complete internal texture information was successfully constructed. Taking the model evaluation method as the judgment standard, the key factors such as image acquisition method and modeling parameters were optimized. The results revealed that employing 200 images and moderate quality modeling can ensure high point cloud density (1.0×10⁵ m), a reasonable number of central feature points (321), a low RMS reprojection error (1.36 pix), and a high modeling efficiency (177 s), meeting the needs of tunnel inspection.

Key words: cable tunnels, photogrammetry, three-dimensional reconstruction, structure from motion, gamma transform, histogram equalization

CLC Number:

TP391

GE Hai-ming, ZHANG Wei, WANG Xiao-long, ZHU Jing-jing, JIA Fei, XUE Ya-dong. Optimization of 3D reconstruction method for urban cable tunnel based on SfM method[J]. Journal of Graphics, 2023, 44(3): 540-550.

Figures/Tables 17

Fig. 1 SfM algorithm flow

Fig. 2 Image histogram equalization processing ((a) The original image and the RGB pixel channel histogram; (b) Balanced image and RGB pixel channel histogram)

Fig. 3 Transform curves with different values (All cases: c=1)

Fig. 4 The effect of the gamma transform of the tunnel image with different γ values ((a) γ=1.0; (b) γ=0.9; (c) γ=0.8; (d) γ=0.7; (e) γ=0.6; (f) γ=0.5; (g) γ=0.4; (h) γ=0.3)

Fig. 5 Extraction results of feature points

Fig. 6 Matching results of feature points ((a) 0.1 m interval; (b) 0.4 m interval)

Fig. 7 Camera position and cable tunnel sparse point cloud

Fig. 8 Cable tunnel dense point cloud

Fig. 9 Cable tunnel model reconstruction ((a) Mesh division; (b) Model reconstruction)

Fig. 10 Texture space

Fig. 11 Cable tunnel 3D texture model

Fig. 12 Cable tunnel tiled texture model

Fig. 13 Root mean square reprojection error for each condition

Fig. 14 Point cloud density for each condition

Fig. 15 Modeling time for each condition

Fig. 16 Number of feature points for each condition ((a) 50 images; (b) 100 images; (c) 200 images; (d) 500 images)

Fig. 17 The number of characteristic points of each condition ((a) Low quality; (b) Medium quality; (c) High quality)

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