利用开放地理信息数据自动生成铁路项目高精度建筑信息模型。
Textured As-Is BIM via GIS-informed Point Cloud Segmentation
- 融合GIS数据与点云分割，实现自动化语义建模。
- 在铁路项目中验证了高效生成可直接用于BIM的三维模型。
- 挖掘免费公开地理数据潜力，降低建模成本。
从零创建现状模型至今仍耗时耗力，主要因人工工作量大。尤其对于空间范围大的项目，从测绘数据（如点云数据PCD）中自动生成具有语义信息的3D几何结构极具价值。可通过机器学习和深度学习模型实现点云的对象识别与语义分割。由于点云通常仅包含点的位置和RGB颜色信息，引入语义丰富的地理信息系统（GIS）数据可显著提升建模效果。本文提出一种方法论、实现框架及概念验证，用于铁路项目中自动化生成基于GIS信息且符合BIM标准的现状建筑信息模型（as-is BIM）。结果表明该方法具备显著成本节约潜力，并揭示了免费可获取的GIS数据尚有未被充分利用的价值。
原文摘要 · Abstract (English)
Creating as-is models from scratch is to this day still a time- and money-consuming task due to its high manual effort. Therefore, projects, especially those with a big spatial extent, could profit from automating the process of creating semantically rich 3D geometries from surveying data such as Point Cloud Data (PCD). An automation can be achieved by using Machine and Deep Learning Models for object recognition and semantic segmentation of PCD. As PCDs do not usually include more than the mere position and RGB colour values of points, tapping into semantically enriched Geoinformation System (GIS) data can be used to enhance the process of creating meaningful as-is models. This paper presents a methodology, an implementation framework and a proof of concept for the automated generation of GIS-informed and BIM-ready as-is Building Information Models (BIM) for railway projects. The results show a high potential for cost savings and reveal the unemployed resources of freely accessible GIS data within.
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