Abstract
Abstract. With the accelerated development of the global economy, the scale of UHV (Ultra High Voltage) large-capacity transmission lines has increased dramatically. Nevertheless, existing transmission line inspection methods rely on human inspectors detecting abnormal facilities from ground level or helicopters. Those methods not only require extremely high labor and equipment costs, but also are time-consuming. In this paper, a thin object 3D reconstruction method is proposed for the extraction of 3D structures of power lines from sequential oblique UAV images. The proposed method recovers the 3D structure of the power lines from three sequential images that depict the structure of power lines in 2D. Proposed method was tested in a typical transmission line corridor and the reconstructed results show the effectiveness of the proposed method.
Highlights
Modern society has particular dependence on electrical energy
A 3D thin structure reconstruction method was proposed for power line by utilizing sequential oblique images collected by low-cost camera loaded on min-UAVs
In the light of these considerations, we address this challenging problem about featureless lines by obtaining candidate 3D curve segments and selecting out the correct 3D curves and recovering a decomposition of such wires into a set of continuous and different wires by utilizing a multiple traveling salesman problem(mTSP) (Worboys et al, 1986)
Summary
Modern society has particular dependence on electrical energy. The importance of building an electrical power system capable of an uninterrupted, safe and sustainable power supply cannot be overstated. Considering the unique characteristics of the reconstruction wiry objects in this study, such as lack of distinctive image features, uniform color, thin elements, and severe self-occlusion(Liu et al, 2017), its extremely hard to digitize the wiry lines, by either using commodity depth sensors or traditional multi-view stereo (MVS) approaches (Seitz et al, n.d.). Both of the methods suffer from obvious noise, loss of data and failed to detect global curve topology, resulting in plausible reconstruction outputs.
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