APPLICATION OF A SHELLNET BASED APPROACH TO SEMANTIC SEGMENTATION IN URBAN POINT CLOUD

Author:

Chen D.,Ma X.,Lu X.,Xiao J.

Abstract

Abstract. In recent years, the popularity of airborne, vehicle-borne, and terrestrial 3D laser scanners has driven the rapid development of 3D point cloud processing methods. The 3D laser scanning technology has the characteristics of non-contact, high density, high accuracy, and digitalization, which can achieve comprehensive and fast 3D scanning of urban point clouds. To address the current situation that it is difficult to accurately segment urban point clouds in complex scenes from 3D laser scanned point clouds, a technical process for accurate and fast semantic segmentation of urban point clouds is proposed. In this study, the point clouds are first denoised, then the samples are annotated and sample sets are created based on the point cloud features of the category targets using CloudCompare software, followed by an end-to-end trainable optimization network-ShellNet, to train the urban point cloud samples, and finally, the models are evaluated on a test set. The method achieved IoU metrics of 89.83% and 73.74% for semantic segmentation of buildings and rods-like objects respectively. From the visualization results of the test set, the algorithm is feasible and robust, providing a new idea and method for semantic segmentation of large-scale urban scenes.

Publisher

Copernicus GmbH

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3