Automatic reconstruction of multi-level indoor spaces from point cloud and trajectory

Gahyeon Lim, Nakju Doh

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Remarkable progress in the development of modeling methods for indoor spaces has been made in recent years with a focus on the reconstruction of complex environments, such as multi-room and multi-level buildings. Existing methods represent indoor structure models as a combination of several sub-spaces, which are constructed by room segmentation or horizontal slicing approach that divide the multi-room or multi-level building environments into several segments. In this study, we propose an automatic reconstruction method of multi-level indoor spaces with unique models, including inter-room and inter-floor connections from point cloud and trajectory. We construct structural points from registered point cloud and extract piece-wise planar segments from the structural points. Then, a three-dimensional space decomposition is conducted and water-tight meshes are generated with energy minimization using graph cut algorithm. The data term of the energy function is expressed as a difference in visibility between each decomposed space and trajectory. The proposed method allows modeling of indoor spaces in complex environments, such as multi-room, room-less, and multi-level buildings. The performance of the proposed approach is evaluated for seven indoor space datasets.

Original languageEnglish
Article number3493
JournalSensors
Volume21
Issue number10
DOIs
Publication statusPublished - 2021 May 2

Keywords

  • Automatic 3D modeling
  • Multi-level building reconstruc-tion
  • Point cloud processing
  • Structured 3D reconstruction

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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