An efficient method to detect mutual overlap of a large set of unordered images for structure-from-motion

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dc.identifier.uri http://dx.doi.org/10.15488/5164
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/5211
dc.contributor.author Wang, X.
dc.contributor.author Zhan, Z.Q.
dc.contributor.author Heipke, Christian
dc.date.accessioned 2019-08-15T07:18:14Z
dc.date.available 2019-08-15T07:18:14Z
dc.date.issued 2017
dc.identifier.citation X. Wang; Z.Q. Zhan; Christian Heipke: An efficient method to detect mutual overlap of a large set of unordered images for structure-from-motion. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2017 (2017), S. 191-198. DOI: https://doi.org/10.5194/isprs-annals-iv-1-w1-191-2017
dc.description.abstract Recently, low-cost 3D reconstruction based on images has become a popular focus of photogrammetry and computer vision research. Methods which can handle an arbitrary geometric setup of a large number of unordered and convergent images are of particular interest. However, determining the mutual overlap poses a considerable challenge. We propose a new method which was inspired by and improves upon methods employing random k-d forests for this task. Specifically, we first derive features from the images and then a random k-d forest is used to find the nearest neighbours in feature space. Subsequently, the degree of similarity between individual images, the image overlaps and thus images belonging to a common block are calculated as input to a structure-from-motion (sfm) pipeline. In our experiments we show the general applicability of the new method and compare it with other methods by analyzing the time efficiency. Orientations and 3D reconstructions were successfully conducted with our overlap graphs by sfm. The results show a speed-up of a factor of 80 compared to conventional pairwise matching, and of 8 and 2 compared to the VocMatch approach using 1 and 4 CPU, respectively. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartofseries ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2017 (2017)
dc.rights CC BY 3.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject 3D reconstruction eng
dc.subject Photogrammetry eng
dc.subject Graph eng
dc.subject Structure from motion eng
dc.subject Artificial intelligence eng
dc.subject Orientation (computer vision) eng
dc.subject Pattern recognition eng
dc.subject Computer vision eng
dc.subject Pairwise comparison eng
dc.subject Feature vector eng
dc.subject Computer science eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 550 | Geowissenschaften ger
dc.title An efficient method to detect mutual overlap of a large set of unordered images for structure-from-motion eng
dc.type Article
dc.type Text
dc.relation.issn 2194-9050
dc.relation.doi https://doi.org/10.5194/isprs-annals-iv-1-w1-191-2017
dc.bibliographicCitation.volume 2017
dc.bibliographicCitation.firstPage 191
dc.bibliographicCitation.lastPage 198
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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