Segmentation and 3d Modeling Methods for Structural Analysis by Machine Learning Algorithms on Point Clouds of Traditional Wooden Buildings
Year: 2024
Type: article
Abstract: The purpose of this study is to develop a system to automatically generate a structural analysis model from a laser-scanned point cloud of a traditional wooden building. To achieve this, it is necessary to develop a segmentation method that extracts only the point cloud of structural members from the point cloud of the entire building without manual selection. As a solution to this problem, we developed a segmentation method using an unsupervised learning algorithm. The application of this algorithm automates a large part of the process involved in segmentation and reduces the amount of effort required.
DOI: 10.3130/aijs.89.1176
Authors: Ryo KASHIBA, Meguru HIRAOKA, Eisuke MITSUDA
Institutions: Taisei (Japan), Kyoto Institute of Technology
Language: English
Subfield: Geology
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4402974077