Abstract
Intelligent navigation and facility management in complex indoor environments are issues at the forefront of geospatial information science. Indoor spaces with fine geometric and semantic descriptions provide a solid foundation for various indoor applications, but it is difficult to comprehensively extract free multi-floor indoor spaces from complex three-dimensional building models, such as those described using CityGML LoD4, with existing methods for the subdivision or extraction of indoor spaces based on vector topology processing. Therefore, this paper elaborates a new voxelbased approach for extracting free multi-floor indoor spaces from 3D building models. It transforms the complicated vector processing tasks into a simple raster process that consists of three steps: voxelization with semantic enhancement, voxel classification, and boundary extraction. Experiments illustrate that the proposed method can automatically and correctly extract free multi-floor indoor spaces, especially two typical kinds of open indoor spaces, namely, lobbies and staircases.
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