Abstract
The automatic modeling of as-built building interiors, known as indoor building reconstruction, is gaining increasing attention because of its widespread applications. With the development of sensors to acquire high-quality point clouds, a new modeling scheme called scan-to-BIM (building information modeling) emerged as well. However, the traditional scan-to-BIM process is time-tedious and labor-intensive. Most existing automatic indoor building reconstruction solutions can only fit the specific data or lack of detailed model representation. In this paper, we propose a layer-wise method, on the basis of 3D planar primitives, to create 2D floor plans and 3D building models. It can deal with different types of point clouds and retain many structural details with respect to protruding structures, complicated ceilings, and fine corners. The experimental results indicate the effectiveness of the proposed method and the robustness against noises and sparse data.
Highlights
Building information modelings (BIMs) of as-built constructions which contain both geometric and semantic information are capable of assisting the facility management, reducing the operation cost, inspecting the construction quality etc
We propose a new method for automatic indoor as-built modeling for both mobile and terrestrial point clouds
This paper proposes a layer-wise method for indoor as-built spaces modeling using 3D planar primitives
Summary
Building information modelings (BIMs) of as-built constructions which contain both geometric and semantic information are capable of assisting the facility management, reducing the operation cost, inspecting the construction quality etc. It is highly required in communities such as Architecture, Engineering, Construction, and Facility Management (AEC/FM) [1]. Compared with BIMs generated from outdoors, the indoor perspective provides structural elements (e.g., floors, ceilings, windows, doors) as well as indoor belongings (e.g., furniture, appliances). In light of this, scanning point clouds are gaining increasing attention as the major metadata of indoor building modeling
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