Smith, William Alfred Peter orcid.org/0000-0002-6047-0413, Lewinska, Paulina Barbara Wiktoria, Cooper, Michael Anthony orcid.org/0000-0002-4054-6783 et al. (3 more authors) (2022) Structure-from-motion with varying principal point. IEEE Geoscience and Remote Sensing Letters. 2001105. ISSN 1545-598X
Abstract
We consider the problem of structure-from-motion (SfM) for images with fixed calibration but varying principal point. This scenario occurs for archival imagery taken using historic glass plate and film cameras without fiducial markers, when images have been inconsistently cropped or when image plates are broken into multiple fragments.We derive initialisation and pose estimation methods and regularisation penalties tuned specifically for this scenario leading to a complete archival imagery SfM pipeline. This problem is of special importance if imiage data set is limited. We illustrate the performance of our methods on challenging real world examples from image archives. Specifically, we use archival images of the East coast of Greenland from the British Arctic Air Route Expedition (BAARE). This is of particular glaciological interest for measuring historic ice loss. We use a modern digital elevation model (ArcticDEM), masked to stable regions, as ground truth to evaluate our method.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) The University of York > Faculty of Sciences (York) > Environment and Geography (York) |
Depositing User: | Pure (York) |
Date Deposited: | 31 May 2022 10:50 |
Last Modified: | 27 Nov 2024 00:43 |
Published Version: | https://doi.org/10.1109/LGRS.2022.3179645 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/LGRS.2022.3179645 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187559 |