dc.identifier.uri |
http://dx.doi.org/10.15488/3761 |
|
dc.identifier.uri |
https://www.repo.uni-hannover.de/handle/123456789/3795 |
|
dc.contributor.author |
Wang, X.
|
|
dc.contributor.author |
Rottensteiner, F.
|
|
dc.contributor.author |
Heipke, C.
|
|
dc.contributor.editor |
Fuse, T.
|
|
dc.contributor.editor |
Remondino, F.
|
|
dc.contributor.editor |
Toschi, I.
|
|
dc.date.accessioned |
2018-10-08T11:54:15Z |
|
dc.date.available |
2018-10-08T11:54:15Z |
|
dc.date.issued |
2018 |
|
dc.identifier.citation |
Wang, X.; Rottensteiner, F.; Heipke, C.: Robust image orientation based on relative rotations and tie points. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 4 (2018), Nr. 2, S. 295-302. DOI: https://doi.org/10.5194/isprs-annals-IV-2-295-2018 |
|
dc.description.abstract |
In this paper we present a novel approach for image orientation by combining relative rotations and tie points. First, we choose an initial image pair with enough correspondences and large triangulation angle, and we then iteratively add clusters of new images. The rotation of these newly added images is estimated from relative rotations by single rotation averaging. In the next step, a linear equation system is set up for each new image to solve the translation parameters with triangulated tie points which can be viewed in that new image, followed by a resection for refinement. Finally, we optimize the cluster of reconstructed images by local bundle adjustment. We show results of our approach on different benchmark datasets. Furthermore, we orient several larger datasets incl. unordered image datasets to demonstrate the robustness and performance of our approach. |
eng |
dc.language.iso |
eng |
|
dc.publisher |
Göttingen : Copernicus GmbH |
|
dc.relation.ispartof |
ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020" : 4-7 June 2018, Riva del Garda, Italy |
|
dc.relation.ispartofseries |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; IV-2 |
|
dc.rights |
CC BY 4.0 Unported |
|
dc.rights.uri |
https://creativecommons.org/licenses/by/4.0/ |
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dc.subject |
image orientation |
eng |
dc.subject |
single rotation averaging |
eng |
dc.subject |
structure from motion (SfM) |
eng |
dc.subject |
translation estimation |
eng |
dc.subject.classification |
Konferenzschrift |
ger |
dc.subject.ddc |
600 | Technik
|
ger |
dc.title |
Robust image orientation based on relative rotations and tie points |
eng |
dc.type |
Article |
|
dc.type |
Text |
|
dc.relation.essn |
2194-9050 |
|
dc.relation.issn |
21949042 |
|
dc.relation.doi |
https://doi.org/10.5194/isprs-annals-IV-2-295-2018 |
|
dc.bibliographicCitation.issue |
2 |
|
dc.bibliographicCitation.volume |
IV-2 |
|
dc.bibliographicCitation.firstPage |
295 |
|
dc.bibliographicCitation.lastPage |
302 |
|
dc.description.version |
publishedVersion |
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tib.accessRights |
frei zug�nglich |
|