An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring
Estimating 3D deformation with high spatial resolution from TLS point clouds is beneficial for geomonitoring. Existing methods for this task primarily rely on geometric data. They do not use radiometric information although it is often available as well. This leaves potential for improvement. To add...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
|
| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-annals.copernicus.org/articles/X-G-2025/953/2025/isprs-annals-X-G-2025-953-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849721598842503168 |
|---|---|
| author | Z. Wang J. A. Butt J. A. Butt S. Huang N. Meyer T. Medić A. Wieser |
| author_facet | Z. Wang J. A. Butt J. A. Butt S. Huang N. Meyer T. Medić A. Wieser |
| author_sort | Z. Wang |
| collection | DOAJ |
| description | Estimating 3D deformation with high spatial resolution from TLS point clouds is beneficial for geomonitoring. Existing methods for this task primarily rely on geometric data. They do not use radiometric information although it is often available as well. This leaves potential for improvement. To address this, we propose an approach that utilizes RGB images—captured by built-in cameras of TLS scanners and co-registered with TLS point clouds—to generate dense 3D displacement vector fields for deformation analysis. Our method comprises three main steps: (1) applying the Efficient-LoFTR algorithm to establish dense 2D pixel correspondences on RGB images across two epochs; (2) projecting 3D points from both epochs onto RGB images and establishing 3D point correspondences by matching the projected pixels with the established 2D correspondences; (3) clustering the point cloud of one epoch and refining the 3D point correspondences within each cluster to produce the final displacement vector fields. Experiments on real measurements obtained from a rockfall simulator and from a real-world landslide demonstrate that our method achieves comparable accuracy to state-of-the-art geometry-based methods, with improved density and computational efficiency. By using radiometric features, our approach complements geometry-based methods, suggesting that combining both will enhance coverage and/or accuracy for geomonitoring applications. |
| format | Article |
| id | doaj-art-0f58c7b1bc9e457489ee3e696945f2f5 |
| institution | DOAJ |
| issn | 2194-9042 2194-9050 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj-art-0f58c7b1bc9e457489ee3e696945f2f52025-08-20T03:11:37ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502025-07-01X-G-202595396010.5194/isprs-annals-X-G-2025-953-2025An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based GeomonitoringZ. Wang0J. A. Butt1J. A. Butt2S. Huang3N. Meyer4T. Medić5A. Wieser6Institute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandInstitute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandAtlas optimization GmbH, SwitzerlandInstitute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandInstitute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandInstitute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandInstitute of Geodesy and Photogrammetry, ETH Zürich, SwitzerlandEstimating 3D deformation with high spatial resolution from TLS point clouds is beneficial for geomonitoring. Existing methods for this task primarily rely on geometric data. They do not use radiometric information although it is often available as well. This leaves potential for improvement. To address this, we propose an approach that utilizes RGB images—captured by built-in cameras of TLS scanners and co-registered with TLS point clouds—to generate dense 3D displacement vector fields for deformation analysis. Our method comprises three main steps: (1) applying the Efficient-LoFTR algorithm to establish dense 2D pixel correspondences on RGB images across two epochs; (2) projecting 3D points from both epochs onto RGB images and establishing 3D point correspondences by matching the projected pixels with the established 2D correspondences; (3) clustering the point cloud of one epoch and refining the 3D point correspondences within each cluster to produce the final displacement vector fields. Experiments on real measurements obtained from a rockfall simulator and from a real-world landslide demonstrate that our method achieves comparable accuracy to state-of-the-art geometry-based methods, with improved density and computational efficiency. By using radiometric features, our approach complements geometry-based methods, suggesting that combining both will enhance coverage and/or accuracy for geomonitoring applications.https://isprs-annals.copernicus.org/articles/X-G-2025/953/2025/isprs-annals-X-G-2025-953-2025.pdf |
| spellingShingle | Z. Wang J. A. Butt J. A. Butt S. Huang N. Meyer T. Medić A. Wieser An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring |
| title_full | An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring |
| title_fullStr | An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring |
| title_full_unstemmed | An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring |
| title_short | An Approach for RGB-Guided Dense 3D Displacement Estimation in TLS-Based Geomonitoring |
| title_sort | approach for rgb guided dense 3d displacement estimation in tls based geomonitoring |
| url | https://isprs-annals.copernicus.org/articles/X-G-2025/953/2025/isprs-annals-X-G-2025-953-2025.pdf |
| work_keys_str_mv | AT zwang anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT jabutt anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT jabutt anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT shuang anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT nmeyer anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT tmedic anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT awieser anapproachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT zwang approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT jabutt approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT jabutt approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT shuang approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT nmeyer approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT tmedic approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring AT awieser approachforrgbguideddense3ddisplacementestimationintlsbasedgeomonitoring |