Global rotation estimation using weighted iterative lie algebraic averaging

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dc.identifier.uri http://dx.doi.org/10.15488/5002
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/5046
dc.contributor.author Reich, Martin
dc.contributor.author Heipke, Christian
dc.date.accessioned 2019-06-26T11:10:02Z
dc.date.available 2019-06-26T11:10:02Z
dc.date.issued 2015
dc.identifier.citation Reich, Martin; Heipke, Christian: Global rotation estimation using weighted iterative lie algebraic averaging. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (2015), S. 443-449. DOI: https://doi.org/10.5194/isprsannals-ii-3-w5-443-2015
dc.description.abstract In this paper we present an approach for a weighted rotation averaging to estimate absolute rotations from relative rotations between two images for a set of multiple overlapping images. The solution does not depend on initial values for the unknown parameters and is robust against outliers. Our approach is one part of a solution for a global image orientation. Often relative rotations are not free from outliers, thus we use the redundancy in available pairwise relative rotations and present a novel graph-based algorithm to detect and eliminate inconsistent rotations. The remaining relative rotations are input to a weighted least squares adjustment performed in the Lie algebra of the rotation manifold SO (3) to obtain absolute orientation parameters for each image. Weights are determined using the prior information we derived from the estimation of the relative rotations. Because we use the Lie algebra of SO (3) for averaging no subsequent adaptation of the results has to be performed but the lossless projection to the manifold. We evaluate our approach on synthetic and real data. Our approach often is able to detect and eliminate all outliers from the relative rotations even if very high outlier rates are present. We show that we improve the quality of the estimated absolute rotations by introducing individual weights for the relative rotations based on various indicators. In comparison with the state-of-the-art in recent publications to global image orientation we achieve best results in the examined datasets. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartofseries ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (2015)
dc.rights CC BY 3.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Mathematical optimization eng
dc.subject Least squares eng
dc.subject Pairwise comparison eng
dc.subject Cross-validation eng
dc.subject Mathematics eng
dc.subject Lie algebra eng
dc.subject Pose eng
dc.subject Outlier eng
dc.subject Lossless compression eng
dc.subject Orientation (computer vision) eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title Global rotation estimation using weighted iterative lie algebraic averaging
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2194-9050
dc.relation.doi https://doi.org/10.5194/isprsannals-ii-3-w5-443-2015
dc.bibliographicCitation.volume II-3/W5
dc.bibliographicCitation.firstPage 443
dc.bibliographicCitation.lastPage 449
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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