Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/10714
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dc.contributor.authorBaştanlar, Yalın-
dc.contributor.authorTemizel, Alptekin-
dc.contributor.authorYardımcı, Y.-
dc.contributor.authorSturm, P.-
dc.date.accessioned2021-01-24T18:47:37Z-
dc.date.available2021-01-24T18:47:37Z-
dc.date.issued2012-
dc.identifier.issn0262-8856-
dc.identifier.issn1872-8138-
dc.identifier.urihttps://doi.org/10.1016/j.imavis.2012.06.001-
dc.identifier.urihttps://hdl.handle.net/10714-
dc.description.abstractWe describe a pipeline for structure-from-motion (SfM) with mixed camera types, namely omnidirectional and perspective cameras. For the steps of this pipeline, we propose new approaches or adapt the existing perspective camera methods to make the pipeline effective and automatic. We model our cameras of different types with the sphere camera model. To match feature points, we describe a preprocessing algorithm which significantly increases scale invariant feature transform (SIFT) matching performance for hybrid image pairs. With this approach, automatic point matching between omnidirectional and perspective images is achieved. We robustly estimate the hybrid fundamental matrix with the obtained point correspondences. We introduce the normalization matrices for lifted coordinates so that normalization and denormalization can be performed linearly for omnidirectional images. We evaluate the alternatives of estimating camera poses in hybrid pairs. A weighting strategy is proposed for iterative linear triangulation which improves the structure estimation accuracy. Following the addition of multiple perspective and omnidirectional images to the structure, we perform sparse bundle adjustment on the estimated structure by adapting it to use the sphere camera model. Demonstrations of the end-to-end multi-view SfM pipeline with the real images of mixed camera types are presented. (C) 2012 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevier Ltd.en_US
dc.relation.ispartofImage and Vision Computingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOmnidirectional camerasen_US
dc.subjectHybrid camera systemsen_US
dc.subjectFeature matchingen_US
dc.subjectEpipolar geometryen_US
dc.subjectMulti-viewen_US
dc.subjectStructure-from-motionen_US
dc.titleMulti-view structure-from-motion for hybrid camera scenariosen_US
dc.typeArticleen_US
dc.departmentIzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.volume30en_US
dc.identifier.issue8en_US
dc.identifier.startpage557en_US
dc.identifier.endpage572en_US
dc.identifier.wosWOS:000308904100016-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.cont.department-temp[Bastanlar, Y.; Temizel, A.; Yardimci, Y.] Middle E Tech Univ, Inst Informat, TR-06531 Ankara, Turkey; [Sturm, P.] INRIA Rhone Alpes, Grenoble, France; [Sturm, P.] Lab Jean Kuntzmann, Grenoble, Franceen_US
dc.identifier.doi10.1016/j.imavis.2012.06.001-
dc.relation.doi10.1016/j.imavis.2012.06.001en_US
dc.coverage.doi10.1016/j.imavis.2012.06.001en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.deptDepartment of Computer Engineering-
Appears in Collections:WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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