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dc.contributor.authorHast, Anders
dc.contributor.authorMarchetti, Andrea
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-10-10T06:38:48Z
dc.date.available2017-10-10T06:38:48Z
dc.date.issued2014
dc.identifier.citationWSCG 2014: communication papers proceedings: 21st International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 49-56.en
dc.identifier.isbn978-80-86943-71-8
dc.identifier.uriwscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26377
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2014: communication papers proceedingsen
dc.rights@ Václav Skala - UNION Agencycs
dc.subjectdetektor zájmových bodůcs
dc.subjectfunkcecs
dc.subjectinvariancecs
dc.subjectspinorový tenzorcs
dc.subjectHarrisův detektorcs
dc.subjectHessianova maticecs
dc.titleInvariant interest point detection based on variations of the spinor tensoren
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedImage features are obtained by using some kind of interest point detector, which often is based on a symmetric matrix such as the structure tensor or the Hessian matrix. These features need to be invariant to rotation and to some degree also to scaling in order to be useful for feature matching in applications such as image registration. Recently, the spinor tensor has been proposed for edge detection. It was investigated herein how it also can be used for feature matching and it will be proven that some simplifications, leading to variations of the response function based on the tensor, will improve its characteristics. The result is a set of different approaches that will be compared to the well known methods using the Hessian and the structure tensor. Most importantly the invariance when it comes to rotation and scaling will be compared.en
dc.subject.translatedinterest point detectoren
dc.subject.translatedfeaturesen
dc.subject.translatedinvarianceen
dc.subject.translatedspinor tensoren
dc.subject.translatedHarris detectoren
dc.subject.translatedHessian matrixen
dc.type.statusPeer-revieweden
Appears in Collections:WSCG 2014: Communication Papers Proceedings

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