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BIM for existing facilities: feasibility of spectral image integration to 3D point cloud data

机译:现有设施的BIM:将光谱图像集成到3D点云数据的可行性

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Accurate geometrical and spatial information of the built environment can be accurately acquired and the resulting 3D point cloud data is required to be processed to construct the digital model, Building Information Modelling (BIM) for existing facilities. Point cloud by laser scanning over the buildings and facilities has been commonly used, but the data requires external information so that any objects and materials can be correctly identified and classified. A number of advanced data processing methods have been developed, such as the use of colour information to attach semantic information. However, the accuracy of colour information depends largely on the scene environment where the image is acquired. The limited number of spectral channels on conventional RGB camera often fails to extract important information about surface material, despite spectral surface reflectance can represent a signature of the material. Hyperspectral imaging can, instead, provide precise representation of spatial and spectral information. By implementing such information to 3D point cloud, the efficiency of material detection and classification in BIM should be significantly improved. In this work, the feasibility of the image integration and discuss practical difficulties in the development.
机译:可以准确获取建筑环境的准确几何和空间信息,并且需要处理生成的3D点云数据以构建数字模型,即现有设施的建筑信息模型(BIM)。通常通过激光扫描建筑物和设施上的点云,但是数据需要外部信息,以便可以正确识别和分类任何物体和材料。已经开发了许多高级数据处理方法,例如使用颜色信息附加语义信息。但是,颜色信息的准确性在很大程度上取决于获取图像的场景环境。尽管光谱表面反射率可以代表材料的特征,但常规RGB相机上有限数量的光谱通道通常无法提取有关表面材料的重要信息。相反,高光谱成像可以提供空间和光谱信息的精确表示。通过将此类信息实施到3D点云,应该显着提高BIM中材料检测和分类的效率。在这项工作中,图像整合的可行性和讨论了开发中的实际困难。

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