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Automatic voxel-based 3D indoor reconstruction and room partitioning from triangle meshes

Hübner, Patrick 1; Weinmann, Martin 1; Wursthorn, Sven 1; Hinz, Stefan 1
1 Institut für Photogrammetrie und Fernerkundung (IPF), Karlsruher Institut für Technologie (KIT)


With the gaining popularity and proliferation of building information modeling (BIM) techniques, a growing demand emerges for accurate, up-to-date and semantically-enriched digital representations of built environments. In this regard, current mobile indoor mapping systems like the Microsoft HoloLens or Matterport allow to efficiently acquire triangle meshes of indoor building environments. However, manually reconstructing digital models of building interiors on the basis of these triangle meshes is a cumbersome and time-consuming task. Consequently, in this work, we propose a fully automatic, voxel-based indoor reconstruction approach to derive semantically-enriched and geometrically completed indoor models in voxel representation from unstructured triangle meshes. The presented approach does not require room surfaces such as walls, ceilings or floors to be planar or aligned with the coordinate axes. Furthermore, it does not rely on a clear vertical subdivision in distinct floor levels and even allows for slanted floors such as ramps or stair flights. It thus can also be applied to challenging indoor environments featuring curved room surfaces and complex vertical room layouts. ... mehr

DOI: 10.1016/j.isprsjprs.2021.07.002
Zitationen: 20
Web of Science
Zitationen: 17
Zitationen: 21
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 11.2021
Sprache Englisch
Identifikator ISSN: 0924-2716
KITopen-ID: 1000138003
Erschienen in ISPRS journal of photogrammetry and remote sensing
Verlag Elsevier
Band 181
Seiten 254–278
Vorab online veröffentlicht am 24.09.2021
Schlagwörter Indoor reconstruction, 3D,, Triangle mesh, Voxelization, Classification, Evaluation, Benchmark data, Microsoft HoloLens
Nachgewiesen in Dimensions
Web of Science
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