Automatic Reconstruction of Multi-Level Indoor Spaces from Point Cloud and Trajectory
- Authors
- Lim, Gahyeon; Doh, Nakju
- Issue Date
- 5월-2021
- Publisher
- MDPI
- Keywords
- automatic 3D modeling; multi-level building reconstruction; point cloud processing; structured 3D reconstruction
- Citation
- SENSORS, v.21, no.10
- Indexed
- SCIE
SCOPUS
- Journal Title
- SENSORS
- Volume
- 21
- Number
- 10
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/137432
- DOI
- 10.3390/s21103493
- ISSN
- 1424-8220
- 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.
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Collections - Graduate School > Department of Life Sciences > 1. Journal Articles
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