An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds
Three-dimensional laser scanning technology has increasingly gained favor among professionals in tunnel monitoring. A fundamental challenge in tunnel point cloud processing is to efficiently manage massive datasets using appropriate data structures and accurately extract features such as tunnel axes...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/1/133 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841548999828439040 |
|---|---|
| author | Hongyang Zhang Qigui Yang Quan Liu Yinlong Jin Gang Ma Xin Meng |
| author_facet | Hongyang Zhang Qigui Yang Quan Liu Yinlong Jin Gang Ma Xin Meng |
| author_sort | Hongyang Zhang |
| collection | DOAJ |
| description | Three-dimensional laser scanning technology has increasingly gained favor among professionals in tunnel monitoring. A fundamental challenge in tunnel point cloud processing is to efficiently manage massive datasets using appropriate data structures and accurately extract features such as tunnel axes and cross-sections. However, existing studies often disconnect tunnel point cloud indexing from post-processing tasks. Conventional structures (e.g., voxels, octrees) struggle with long strip-like uneven spatial distribution, resulting in imbalanced trees with numerous empty nodes, which are incompatible with axis-aligned operations. Therefore, this study proposes a dual-layer indexing structure tailored to tunnel geometries. The upper layer reorganizes the tunnel point cloud along its axis, while the lower layer leverages local octrees for fast data querying and updates. In implementation, we introduce a merge-based octree generation strategy for ultra-large-scale datasets, and a rapid Hough transform-based algorithm for tunnel boundaries and axes extraction. Experimental results demonstrate that the proposed method successfully supports the management and visualization of a tunnel point cloud exceeding 6 billion points, significantly enhancing efficiency in narrow tunnel scenarios and streamlining various axis-aligned post-processing tasks. |
| format | Article |
| id | doaj-art-79565e0374f845b59361ad4eb101bc1d |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-79565e0374f845b59361ad4eb101bc1d2025-01-10T13:20:20ZengMDPI AGRemote Sensing2072-42922025-01-0117113310.3390/rs17010133An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point CloudsHongyang Zhang0Qigui Yang1Quan Liu2Yinlong Jin3Gang Ma4Xin Meng5Institute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaInstitute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaInstitute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaInstitute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaInstitute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaInstitute of Water Engineering Sciences, Wuhan University, Wuhan 430072, ChinaThree-dimensional laser scanning technology has increasingly gained favor among professionals in tunnel monitoring. A fundamental challenge in tunnel point cloud processing is to efficiently manage massive datasets using appropriate data structures and accurately extract features such as tunnel axes and cross-sections. However, existing studies often disconnect tunnel point cloud indexing from post-processing tasks. Conventional structures (e.g., voxels, octrees) struggle with long strip-like uneven spatial distribution, resulting in imbalanced trees with numerous empty nodes, which are incompatible with axis-aligned operations. Therefore, this study proposes a dual-layer indexing structure tailored to tunnel geometries. The upper layer reorganizes the tunnel point cloud along its axis, while the lower layer leverages local octrees for fast data querying and updates. In implementation, we introduce a merge-based octree generation strategy for ultra-large-scale datasets, and a rapid Hough transform-based algorithm for tunnel boundaries and axes extraction. Experimental results demonstrate that the proposed method successfully supports the management and visualization of a tunnel point cloud exceeding 6 billion points, significantly enhancing efficiency in narrow tunnel scenarios and streamlining various axis-aligned post-processing tasks.https://www.mdpi.com/2072-4292/17/1/133point cloudtunnel engineeringdual-layer indexing structuremerge-based octree |
| spellingShingle | Hongyang Zhang Qigui Yang Quan Liu Yinlong Jin Gang Ma Xin Meng An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds Remote Sensing point cloud tunnel engineering dual-layer indexing structure merge-based octree |
| title | An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds |
| title_full | An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds |
| title_fullStr | An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds |
| title_full_unstemmed | An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds |
| title_short | An Axial-Oriented Dual-Layer Indexing Structure for Tunnel Point Clouds |
| title_sort | axial oriented dual layer indexing structure for tunnel point clouds |
| topic | point cloud tunnel engineering dual-layer indexing structure merge-based octree |
| url | https://www.mdpi.com/2072-4292/17/1/133 |
| work_keys_str_mv | AT hongyangzhang anaxialorientedduallayerindexingstructurefortunnelpointclouds AT qiguiyang anaxialorientedduallayerindexingstructurefortunnelpointclouds AT quanliu anaxialorientedduallayerindexingstructurefortunnelpointclouds AT yinlongjin anaxialorientedduallayerindexingstructurefortunnelpointclouds AT gangma anaxialorientedduallayerindexingstructurefortunnelpointclouds AT xinmeng anaxialorientedduallayerindexingstructurefortunnelpointclouds AT hongyangzhang axialorientedduallayerindexingstructurefortunnelpointclouds AT qiguiyang axialorientedduallayerindexingstructurefortunnelpointclouds AT quanliu axialorientedduallayerindexingstructurefortunnelpointclouds AT yinlongjin axialorientedduallayerindexingstructurefortunnelpointclouds AT gangma axialorientedduallayerindexingstructurefortunnelpointclouds AT xinmeng axialorientedduallayerindexingstructurefortunnelpointclouds |