US 12,347,136 B2
Method of high-precision 3D reconstruction of existing railway track lines based on UAV multi-view images
Guangshuai Wang, Tianjin (CN); Jiwei Deng, Tianjin (CN); Wenfeng Gao, Tianjin (CN); Hai Zhao, Tianjin (CN); Guanjun Zhang, Tianjin (CN); Kai Wang, Tianjin (CN); Yingjie Zhang, Tianjin (CN); Huxiao Nie, Tianjin (CN); Wenteng Zhang, Tianjin (CN); Liang Yue, Tianjin (CN); Yuhui Ge, Tianjin (CN); Shuai Gao, Tianjin (CN); and Luoming Zhao, Tianjin (CN)
Assigned to CHINA RAILWAY DESIGN CORPORATION, Tianjin (CN)
Filed by CHINA RAILWAY DESIGN CORPORATION, Tianjin (CN)
Filed on Dec. 8, 2022, as Appl. No. 18/063,273.
Application 18/063,273 is a continuation of application No. PCT/CN2021/129311, filed on Nov. 8, 2021.
Claims priority of application No. 202110424507.X (CN), filed on Apr. 20, 2021.
Prior Publication US 2023/0112991 A1, Apr. 13, 2023
Int. Cl. G06T 7/73 (2017.01); G01C 11/34 (2006.01); G06T 11/00 (2006.01)
CPC G06T 7/73 (2017.01) [G01C 11/34 (2013.01); G06T 11/006 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/30172 (2013.01)] 8 Claims
OG exemplary drawing
 
1. A method of high-precision three-dimensional (3D) reconstruction of existing railway track lines based on unmanned aerial vehicle (UAV) multi-view images, comprising:
S1, acquiring initial data comprising original images from UAV multi-view, external azimuth elements of the images, internal parameters of camera, and initial coordinates of a rail top centerline;
S2, back-projecting the initial coordinates of the rail top centerline to the original images using the image external azimuth elements and the internal parameters of camera, and adjusting a location of an image straight segment to obtain a precise image rail top centerline observation value;
S3, optimizing the image rail top centerline observation value using a nonlinear least squares method to obtain an object space coordinate parameter of a rail top straight segment, and connecting adjacent straight segments in sequence using the object space coordinate parameter to obtain complete 3D coordinates of the rail top centerline; and
s of the rail top centerline; and
S4, distinguishing between rail straight and curved segments according to the obtained 3D coordinates of the rail top centerline, and calculating 3D centerline coordinates of each segment in turn to obtain high-precision 3D coordinates of the rail top centerline,
wherein in S4, the distinguishing between the rail straight and curved segments according to the obtained 3D coordinates of the rail top centerline comprises:
for the obtained rail top centerline, calculating an azimuth angle of each segment by taking the rail node as a distinguishing point, and counting minimum and maximum azimuth angles;
forming a rectangular slice space by taking a preset threshold δ as a search width, and counting a number N of rail nodes falling into the rectangular slice space;
if N is greater than the preset threshold, determining that the rail nodes in the rectangular slice space are all straight segment points; otherwise, determining that the rail nodes in the rectangular slice space are curved segment points; and
moving the rectangular slice space upward by a distance of δ/2 by taking a minimum value as a starting point, and continuing to determine the straight/curved segment point until the rectangular slice space reaches the maximum azimuth angle.