International Journal of Automation Technology
Online ISSN : 1883-8022
Print ISSN : 1881-7629
ISSN-L : 1881-7629
Special Issue on Digital Geometry Processing for Large-Scale Structures and Environments
Extraction of Guardrails from MMS Data Using Convolutional Neural Network
Hiroki MatsumotoYuma MoriHiroshi Masuda
著者情報
ジャーナル オープンアクセス

2021 年 15 巻 3 号 p. 258-267

詳細
抄録

Mobile mapping systems can capture point clouds and digital images of roadside objects. Such data are useful for maintenance, asset management, and 3D map creation. In this paper, we discuss methods for extracting guardrails that separate roadways and walkways. Since there are various shape patterns for guardrails in Japan, flexible methods are required for extracting them. We propose a new extraction method based on point processing and a convolutional neural network (CNN). In our method, point clouds and images are segmented into small fragments, and their features are extracted using CNNs for images and point clouds. Then, features from images and point clouds are combined and investigated using whether they are guardrails or not. Based on our experiments, our method could extract guardrails from point clouds with a high success rate.

著者関連情報

この記事は最新の被引用情報を取得できません。

© 2021 Fuji Technology Press Ltd.

This article is licensed under a Creative Commons [Attribution-NoDerivatives 4.0 International] license (https://creativecommons.org/licenses/by-nd/4.0/).
The journal is fully Open Access under Creative Commons licenses and all articles are free to access at IJAT Official Site.
https://www.fujipress.jp/ijat/au-about/
前の記事 次の記事
feedback
Top