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Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method.
Chen, Zhijian; Zhang, Changxing; Tang, Zhiyi; Fang, Kun; Xu, Wei.
Affiliation
  • Chen Z; Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.
  • Zhang C; Intelligent Infrastructure Operation and Maintenance Technology Innovation Team, Yunnan Provincial Department of Education, Kunming University of Science and Technology, Kunming 650500, China.
  • Tang Z; Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.
  • Fang K; Intelligent Infrastructure Operation and Maintenance Technology Innovation Team, Yunnan Provincial Department of Education, Kunming University of Science and Technology, Kunming 650500, China.
  • Xu W; Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.
Sensors (Basel) ; 24(3)2024 Jan 25.
Article in En | MEDLINE | ID: mdl-38339510
ABSTRACT
In this study, we propose a meticulous method for the three-dimensional modeling of slope models using structured light, a swift and cost-effective technique. Our approach aims to enhance the understanding of slope behavior during landslides by capturing and analyzing surface deformations. The methodology involves the initial capture of images at various stages of landslides, followed by the application of the structured light method for precise three-dimensional reconstructions at each stage. The system's low-cost nature and operational convenience make it accessible for widespread use. Subsequently, a comparative analysis is conducted to identify regions susceptible to severe landslide disasters, providing valuable insights for risk assessment. Our findings underscore the efficacy of this system in facilitating a qualitative analysis of landslide-prone areas, offering a swift and cost-efficient solution for the three-dimensional reconstruction of slope models.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Language: En Journal: Sensors (Basel) Year: 2024 Document type: Article Affiliation country: China Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Language: En Journal: Sensors (Basel) Year: 2024 Document type: Article Affiliation country: China Country of publication: Switzerland