无人机倾斜摄影铁路轨道线高精度自动重建

针对既有铁路测绘上线难、作业效率低及测量精度不足的问题,本文提出了一种基于无人机多视图几何原理的铁路轨道线高精度重建方法。首先从无人机影像上提取线特征;然后采用像方测度获得候选匹配线,基于物方距离测度进行Powell优化,获得精确的钢轨线匹配结果;最后,将影像钢轨线匹配结果作为观测值,以钢轨线反投影距离作为测度,最小二乘优化物方钢轨直线段坐标。试验结果表明,本文方法实现了影像轨道线自动匹配与高精度平差解算,像方反投影残差优于0.5像素,轨距和高程的内符合精度分别为0.006和0.005 m。解算成果的平面高程绝对定位精度可达到2 cm左右,平差模型收敛性良好,可以满足工程应用的需要。

High-precision automatic reconstruction of railway line with UAV oblique photography

Aiming at the problems of difficulty in surveying and mapping of existing railway line, low operation efficiency and insufficient measurement accuracy, this paper proposes a high-precision reconstruction algorithm for existing track lines based on the principle of unmanned aerial vehicle (UAV) multi-view geometry. Firstly, extract the straight line segment from the UAV images. Then, the image-based measurements are used to obtain candidate matching lines, and Powell optimization based on the distance are performed to obtain accurate rail line matching results. Finally, using the image rail line matching results as the observation value and the reprojection distance of the rail lines is used as a measure, the coordinate of rail straight line segments is optimized by the least square method. Experimental results show that the proposed method realizes automatic image rail line matching and high-precision adjustment solution. The image-based reprojection residual is better than 0.5 pixels, and the internal coincidence accuracy of railway gauge and rail height are 0.006 m and 0.005 m, respectively. The horizontal and vertical accuracy of the proposed method can reach about 2 cm, and the adjustment model has good convergence, which could meet the requirements of engineering application.