RESEARCH ON AUTOMATIC EXTRACTION OF BLOCK WALL USING POINT CLOUD DATA

• UMEHARA Yoshimasa

  関西大学 先端科学技術推進機構

• TSUKADA Yoshinori

  摂南大学 経営学部

• TANAKA Shigenori

  関西大学 総合情報学部

• KOZUKI Yasunori

  徳島大学 環境防災研究センター

• SHIMONARU Tsuneaki

  株式会社日本インシーク 水工計画・解析部

• HIRANO Nobutoshi

  株式会社日本インシーク 技術本部

Bibliographic Information

Other Title

• 点群データを用いたブロック塀の自動抽出に関する研究

Abstract

 In Japan, there are many disasters such as typhoons, earthquakes, and tsunamis, and it has been pointed out that there is a danger of the collapse of block walls. Therefore, there is an urgent need to understand and inspect the current state of block walls. Tokushima University is conducting a field survey based on the inspection indicators of the Ministry of Land, Infrastructure, Transport and Tourism with the cooperation of prefectures and municipalities. However, since block walls are scattered in various places, there is a limit to covering a wide area in a short time in the current field survey. On the other hand, construction consultants and surveying companies are making increasing use of sensing data such as lasers and cameras. Therefore, in this research, we will refer to the method of improving the maintenance of block walls using sensing data, and propose a technology to automatically extract block walls from point cloud data.

Journal

• Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics)

  Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 77 (2), I_161-I_173, 2021

  Japan Society of Civil Engineers

Keywords

• block wall
• maintenance
• point cloud data
• deep learning
• feature extraction

Details

• CRID: 1390287363462413952
• NII Article ID: 130007998819
• DOI: 10.2208/jscejcei.77.2_i_161
• ISSN: 21856591
• Web Site: https://www.jstage.jst.go.jp/article/jscejcei/77/2/77_I_161/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed