Research on Identification of Road Features from Point Cloud Data Using Deep Learning
| Autor: | Yoshinori Tsukada, Kenji Nakamura, Koki Nakahata, Yoshimasa Umehara, Shigenori Tanaka |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Mechanical Engineering Deep learning 0211 other engineering and technologies Point cloud 02 engineering and technology computer.software_genre Industrial and Manufacturing Engineering Identification (information) 020901 industrial engineering & automation 021105 building & construction Data mining Artificial intelligence business computer |
| Zdroj: | International Journal of Automation Technology. 15:274-289 |
| ISSN: | 1883-8022 1881-7629 |
| Popis: | Laser measurement technology has progressed significantly in recent years, and diverse methods have been developed to measure three-dimensional (3D) objects within environmental spaces in the form of point cloud data. Although such point cloud data are expected to be used in a variety of applications, such data do not possess information on the specific features represented by the points, making it necessary to manually select the target features. Therefore, the identification of road features is essential for the efficient management of point cloud data. As a technology for identifying features from the point cloud data of road spaces, in this research, we propose a method for automatically dividing point cloud data into units of features and identifying features from projected images with added depth information. We experimentally verified that the proposed method accurately identifies and extracts such features. |
| Databáze: | OpenAIRE |
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