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Earth Science Informatics

, Volume 10, Issue 1, pp 69–83 | Cite as

Free multi-floor indoor space extraction from complex 3D building models

  • Qing Xiong
  • Qing Zhu
  • Zhiqiang Du
  • Sisi Zlatanova
  • Yeting Zhang
  • Yan Zhou
  • Yun Li
Research Article

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 voxel-based 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.

Keywords

Free multi-floor indoor space CityGML LoD4 Indoor space extraction Voxel 

Notes

Acknowledgments

This paper was supported by the National Nature Science Foundation of China (No. 41571390, 41471320, and 41471332) and the National High Technology Research and Development Program of China (2015AA123901).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Qing Xiong
    • 1
  • Qing Zhu
    • 1
    • 2
    • 3
  • Zhiqiang Du
    • 1
    • 3
  • Sisi Zlatanova
    • 4
  • Yeting Zhang
    • 1
    • 3
  • Yan Zhou
    • 5
  • Yun Li
    • 2
  1. 1.State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina
  2. 2.Faculty of Geosciences and Environmental EngineeringSouthwest Jiaotong UniversityChengduChina
  3. 3.Collaborative Innovation Center for Geospatial TechnologyWuhanChina
  4. 4.3D Geoinformation, UrbanismDelft University of TechnologyDelftNetherlands
  5. 5.School of Resources and EnvironmentUniversity of Electric Science and Technology of ChinaChengduChina

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