城市环境中噪声点云数据中电线杆的检测

Alex Ferrin, J. Larrea, Miguel Realpe, Daniel Ochoa
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引用次数: 1

摘要

近年来,3D城市地图变得越来越普遍,因此提供了复杂的点云,包括各种城市家具,如杆状物体。电力公司对城市环境中的电线杆检测特别感兴趣,以便保持更新的库存,以便更好地规划和管理。本研究开发了一种基于厄瓜多尔瓜亚基尔市噪声点云数据的电线杆自动检测方法,该地区许多电线杆离建筑物非常近,这增加了区分电线杆、墙、柱、栅栏和建筑物角落的难度。该方法采用基于垂直体素聚类的分割阶段和基于神经网络的分类阶段。
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Detection of utility poles from noisy Point Cloud Data in Urban environments
In recent years 3D urban maps have become more common, thus providing complex point clouds that include diverse urban furniture such as pole-like objects. Utility poles detection in urban environment is of particular interest for electric utility companies in order to maintain an updated inventory for better planning and management. The present study develops an automatic method for the detection of utility poles from noisy point cloud data of Guayaquil - Ecuador, where many poles are located very close to buildings, which increases the difficulty of discriminating poles, walls, columns, fences and building corners. The proposed method applies a segmentation stage based on clustering with vertical voxels and a classification stage based on neural networks.
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