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Volumetric Representation and Sphere Packing of Indoor Space for Three-Dimensional Room Segmentation
Content Provider | MDPI |
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Author | Yang, Fan Che, Mingliang Zuo, Xinkai Li, Lin Zhang, Jiyi Zhang, Chi |
Copyright Year | 2021 |
Description | Room segmentation is a basic task for the semantic enrichment of point clouds. Recent studies have mainly projected single-floor point clouds to binary images to realize two-dimensional room segmentation. However, these methods have difficulty solving semantic segmentation problems in complex 3D indoor environments, including cross-floor spaces and rooms inside rooms; this is the bottleneck of indoor 3D modeling for non-Manhattan worlds. To make full use of the abundant geometric and spatial structure information in 3D space, a novel 3D room segmentation method that realizes room segmentation directly in 3D space is proposed in this study. The method utilizes volumetric representation based on a VDB data structure and packs an indoor space with a set of compact spheres to form rooms as separated connected components. Experimental results on different types of indoor point cloud datasets demonstrate the efficiency of the proposed method. |
Starting Page | 739 |
e-ISSN | 22209964 |
DOI | 10.3390/ijgi10110739 |
Journal | ISPRS International Journal of Geo-Information |
Issue Number | 11 |
Volume Number | 10 |
Language | English |
Publisher | MDPI |
Publisher Date | 2021-10-29 |
Access Restriction | Open |
Subject Keyword | ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Remote Sensing Room Segmentation Point Clouds Volumetric Sphere Packing Indoor Space |
Content Type | Text |
Resource Type | Article |