RESEARCH FOR GENERATING PARAMETRIC MODELS BASED ON EDGE ESTIMATION USING POINT CLOUD DATA OF BRIDGE

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  • 橋梁点群データからのエッジ推定によるパラメトリックモデルの生成に関する研究

Abstract

<p> Recently, the Ministry of Land, Infrastructure, Transport and Tourism has advocated for the application of BIM/CIM principles, to promote design project on digitalization and utilization of 3D models. Such digital transformation Such digital transformation allows stakeholders to be more able to manage data sharing and utilization, which aims to improve productivity in design, construction, maintenance, and management. However, creating 3D models for existing structures on bridges requires measurement data, specialized knowledge, and substantial effort. Previous researches have proposed methods to automatically generate parametric models based on point cloud data and bridge component template models using genetic algorithms. However, these methods need significant processing time. Therefore, in this research, a more efficient method is proposed to generate parametric models by employing deep learning to estimate edge data on bridge component point cloud data, after which wireframe models are subsequently created. The proposed method is possible to generate parametric model with higher accuracy and speed compared to existing methods.</p>

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