A Heuristic Method for Power Pylon Reconstruction from Airborne LiDAR Data

Object reconstruction from airborne LiDAR data is a hot topic in photogrammetry and remote sensing. Power fundamental infrastructure monitoring plays a vital role in power transmission safety. This paper proposes a heuristic reconstruction method for power pylons widely used in high voltage transmission systems from airborne LiDAR point cloud, which combines both data-driven and model-driven strategies. Structurally, a power pylon can be decomposed into two parts: the pylon body and head. The reconstruction procedure assembles two parts sequentially: firstly, the pylon body is reconstructed by a data-driven strategy, where a RANSAC-based algorithm is adopted to fit four principal legs; secondly, a model-driven strategy is used to reconstruct the pylon head with the aid of a predefined 3D head model library, where the pylon head's type is recognized by a shape context algorithm, and their parameters are estimated by a Metropolis-Hastings sampler coupled with a Simulated annealing algorithm. The proposed method has two advantages: (1) optimal strategies are adopted to reconstruct different pylon parts, which are robust to noise and partially missing data; and (2) both the number of parameters and their search space are greatly reduced when estimating the head model's parameters, as the body reconstruction results information about the original point cloud, and relationships between parameters are used in the pylon head reconstruction process. Experimental results show that the proposed method can efficiently reconstruct power pylons, and the average residual between the reconstructed models and the raw data was smaller than 0.3 m.