Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds
Robust and automated point cloud registration methods are required in many geoscience applications using multi-temporal and multi-modal 3D point clouds. Therefore, a 3D keypoint-based coarse registration workflow has been implemented, utilizing the ISS keypoint detector and 3DSmoothNet descriptor. T...
Published in: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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Online Access: | https://doi.org/10.5194/isprs-annals-X-2-2024-113-2024 https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed |
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ftdoajarticles:oai:doaj.org/article:c6fd52494e09401f85be7bd70e6c12ed 2024-09-15T18:07:54+00:00 Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds S. Isfort M. Elias H.-G. Maas 2024-06-01T00:00:00Z https://doi.org/10.5194/isprs-annals-X-2-2024-113-2024 https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed EN eng Copernicus Publications https://isprs-annals.copernicus.org/articles/X-2-2024/113/2024/isprs-annals-X-2-2024-113-2024.pdf https://doaj.org/toc/2194-9042 https://doaj.org/toc/2194-9050 doi:10.5194/isprs-annals-X-2-2024-113-2024 2194-9042 2194-9050 https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-2-2024, Pp 113-120 (2024) Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 article 2024 ftdoajarticles https://doi.org/10.5194/isprs-annals-X-2-2024-113-2024 2024-08-05T17:49:13Z Robust and automated point cloud registration methods are required in many geoscience applications using multi-temporal and multi-modal 3D point clouds. Therefore, a 3D keypoint-based coarse registration workflow has been implemented, utilizing the ISS keypoint detector and 3DSmoothNet descriptor. This paper contributes to keypoint-based registration research through variations of the standard workflow proposed in the literature, applying a two-staged strategy of global and local keypoint matching as well as prototypical keypoint projection and fine registration based on ICP. Further, by testing the utilized detector and descriptor on unstructured, multi-temporal and multi-source point clouds with variations in point cloud density, generalization ability is tested outside benchmark data. Therefore, data of the Bøverbreen glacier in Jotunheimen, Norway has been acquired in 2022 and 2023, deploying UAV-based image matching and terrestrial laser scanning. The results show good performance of the implemented robust matching algorithm PROSAC, requiring fewer iterations than the well-known RANSAC approach, but solving the rigid body transformation with TEASER++ is faster and more robust to outliers without demanding pre-knowledge of the data. Further, the results identify the keypoint detection as most limiting factor in speed and accuracy. Summarizing, keypoint-based coarse registration on low density point clouds, applying a global and local matching strategy and transformation estimation using TEASER++ is recommended. Keypoint projection shows potential, increasing number and precision in low density clouds, but has to be more robust. Further research needs to be carried out, focusing on identifying a fast and robust keypoint detector. Article in Journal/Newspaper glacier Directory of Open Access Journals: DOAJ Articles ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-2-2024 113 120 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 |
spellingShingle |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 S. Isfort M. Elias H.-G. Maas Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
topic_facet |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 |
description |
Robust and automated point cloud registration methods are required in many geoscience applications using multi-temporal and multi-modal 3D point clouds. Therefore, a 3D keypoint-based coarse registration workflow has been implemented, utilizing the ISS keypoint detector and 3DSmoothNet descriptor. This paper contributes to keypoint-based registration research through variations of the standard workflow proposed in the literature, applying a two-staged strategy of global and local keypoint matching as well as prototypical keypoint projection and fine registration based on ICP. Further, by testing the utilized detector and descriptor on unstructured, multi-temporal and multi-source point clouds with variations in point cloud density, generalization ability is tested outside benchmark data. Therefore, data of the Bøverbreen glacier in Jotunheimen, Norway has been acquired in 2022 and 2023, deploying UAV-based image matching and terrestrial laser scanning. The results show good performance of the implemented robust matching algorithm PROSAC, requiring fewer iterations than the well-known RANSAC approach, but solving the rigid body transformation with TEASER++ is faster and more robust to outliers without demanding pre-knowledge of the data. Further, the results identify the keypoint detection as most limiting factor in speed and accuracy. Summarizing, keypoint-based coarse registration on low density point clouds, applying a global and local matching strategy and transformation estimation using TEASER++ is recommended. Keypoint projection shows potential, increasing number and precision in low density clouds, but has to be more robust. Further research needs to be carried out, focusing on identifying a fast and robust keypoint detector. |
format |
Article in Journal/Newspaper |
author |
S. Isfort M. Elias H.-G. Maas |
author_facet |
S. Isfort M. Elias H.-G. Maas |
author_sort |
S. Isfort |
title |
Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
title_short |
Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
title_full |
Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
title_fullStr |
Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
title_full_unstemmed |
Development and Evaluation of a Two-Staged 3D Keypoint Based Workflow for the Co-Registration of Unstructured Multi-Temporal and Multi-Modal 3D Point Clouds |
title_sort |
development and evaluation of a two-staged 3d keypoint based workflow for the co-registration of unstructured multi-temporal and multi-modal 3d point clouds |
publisher |
Copernicus Publications |
publishDate |
2024 |
url |
https://doi.org/10.5194/isprs-annals-X-2-2024-113-2024 https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed |
genre |
glacier |
genre_facet |
glacier |
op_source |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-2-2024, Pp 113-120 (2024) |
op_relation |
https://isprs-annals.copernicus.org/articles/X-2-2024/113/2024/isprs-annals-X-2-2024-113-2024.pdf https://doaj.org/toc/2194-9042 https://doaj.org/toc/2194-9050 doi:10.5194/isprs-annals-X-2-2024-113-2024 2194-9042 2194-9050 https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed |
op_doi |
https://doi.org/10.5194/isprs-annals-X-2-2024-113-2024 |
container_title |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
container_volume |
X-2-2024 |
container_start_page |
113 |
op_container_end_page |
120 |
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