BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION
For conventional SfM pipeline, image matching is enduring limitation when considering the time efficiency. In the last few years, to speed up image matching procedure, many image retrieval works were proposed to fast find overlapping image pairs, e.g., bag-of-word that clusters hand-crafted local fe...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1685/2023/isprs-archives-XLVIII-1-W2-2023-1685-2023.pdf |
| _version_ | 1797391195167522816 |
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| author | H. Zhan Y. F. Yu Y. W. Xu Q. B. Hou R. Xia X. Wang Y. Feng Z. Q. Zhan M. L. Li M. Gruber R. Hänsch C. Heipke |
| author_facet | H. Zhan Y. F. Yu Y. W. Xu Q. B. Hou R. Xia X. Wang Y. Feng Z. Q. Zhan M. L. Li M. Gruber R. Hänsch C. Heipke |
| author_sort | H. Zhan |
| collection | DOAJ |
| description | For conventional SfM pipeline, image matching is enduring limitation when considering the time efficiency. In the last few years, to speed up image matching procedure, many image retrieval works were proposed to fast find overlapping image pairs, e.g., bag-of-word that clusters hand-crafted local features in a hierarchical way for efficient similar image retrieval, or learning-based global features (such as, VGG or ResNet) are used to represent image in a global compact manner. However, there are rarely benchmarks with referenced overlapping information to: first, evaluate the retrieval performance; second, fine tune deep-learning models along the direction that is more capable to deal with overlapping image pairs.<br />In this work, based on traditional photogrammetric procedures, relevant photogrammetric information is obtained including image orientation parameters, 3D mesh model and etc., we then generate a benchmark for determining Overlapping Images - BeDOI, in which referenced pairwise overlapping relationships are estimated via rigorous photogrammetric geometry. To extend the generality, in total, BeDOI contains 13667 images which are basically UAV and close-range images of various scene categories, e.g., urban cities, campus, village, historical relics, green land, buildings and etc. Lastly, to demonstrate the efficacy of the proposed BeDOI, several image retrieval methods are tested and the experimental results are reported as a competition challenge. |
| first_indexed | 2024-03-08T23:28:21Z |
| format | Article |
| id | doaj.art-0b724da81b234fba963e93f51d39199c |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-03-08T23:28:21Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-0b724da81b234fba963e93f51d39199c2023-12-14T16:26:15ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-12-01XLVIII-1-W2-20231685169210.5194/isprs-archives-XLVIII-1-W2-2023-1685-2023BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATIONH. Zhan0Y. F. Yu1Y. W. Xu2Q. B. Hou3R. Xia4X. Wang5Y. Feng6Z. Q. Zhan7M. L. Li8M. Gruber9R. Hänsch10C. Heipke11School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaChair of Cartography and Visual Analytics, Technical University of Munich, GermanySchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430072, People’s Republic of ChinaCollege of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, People’s Republic of ChinaVexcel Imaging GmbH, AustriaMicrowaves and Radar Institute, German Aerospace Center (DLR), GermanyInstitute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, GermanyFor conventional SfM pipeline, image matching is enduring limitation when considering the time efficiency. In the last few years, to speed up image matching procedure, many image retrieval works were proposed to fast find overlapping image pairs, e.g., bag-of-word that clusters hand-crafted local features in a hierarchical way for efficient similar image retrieval, or learning-based global features (such as, VGG or ResNet) are used to represent image in a global compact manner. However, there are rarely benchmarks with referenced overlapping information to: first, evaluate the retrieval performance; second, fine tune deep-learning models along the direction that is more capable to deal with overlapping image pairs.<br />In this work, based on traditional photogrammetric procedures, relevant photogrammetric information is obtained including image orientation parameters, 3D mesh model and etc., we then generate a benchmark for determining Overlapping Images - BeDOI, in which referenced pairwise overlapping relationships are estimated via rigorous photogrammetric geometry. To extend the generality, in total, BeDOI contains 13667 images which are basically UAV and close-range images of various scene categories, e.g., urban cities, campus, village, historical relics, green land, buildings and etc. Lastly, to demonstrate the efficacy of the proposed BeDOI, several image retrieval methods are tested and the experimental results are reported as a competition challenge.https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1685/2023/isprs-archives-XLVIII-1-W2-2023-1685-2023.pdf |
| spellingShingle | H. Zhan Y. F. Yu Y. W. Xu Q. B. Hou R. Xia X. Wang Y. Feng Z. Q. Zhan M. L. Li M. Gruber R. Hänsch C. Heipke BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION |
| title_full | BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION |
| title_fullStr | BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION |
| title_full_unstemmed | BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION |
| title_short | BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION |
| title_sort | bedoi benchmarks for determining overlapping images with photogrammetric information |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1685/2023/isprs-archives-XLVIII-1-W2-2023-1685-2023.pdf |
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