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dc.contributor.authorFernández Alcantarilla, Pablo 
dc.contributor.authorBergasa Pascual, Luis Miguel 
dc.contributor.authorDavison, Andrew
dc.date.accessioned2020-06-25T09:10:34Z
dc.date.available2020-06-25T09:10:34Z
dc.date.issued2013-01
dc.identifier.bibliographicCitationAlcantarilla, P.F., Bergasa, L.M. & Davison, A.J. 2013, "Gauge-SURF descriptors", Image and Vision Computing, vol. 31, no. 1, pp. 103-116
dc.identifier.issn0262-8856
dc.identifier.urihttp://hdl.handle.net/10017/43427
dc.description.abstractIn this paper, we present a novel family of multiscale local feature descriptors, a theoretically and intuitively well justified variant of SURF which is straightforward to implement but which nevertheless is capable of demonstrably better performance with comparable computational cost. Our family of descriptors, called Gauge-SURF (G-SURF), is based on second-order multiscale gauge derivatives. While the standard derivatives used to build a SURF descriptor are all relative to a single chosen orientation, gauge derivatives are evaluated relative to the gradient direction at every pixel. Like standard SURF descriptors, G-SURF descriptors are fast to compute due to the use of integral images, but have extra matching robustness due to the extra invariance offered by gauge derivatives. We present extensive experimental image matching results on the Mikolajczyk and Schmid dataset which show the clear advantages of our family of descriptors against first-order local derivatives based descriptors such as: SURF, Modified-SURF (M-SURF) and SIFT, in both standard and upright forms. In addition, we also show experimental results on large-scale 3D Structure from Motion (SfM) and visual categorization applications.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights© 2013 Elsevier
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGauge coordinatesen
dc.subjectScale spaceen
dc.subjectFeature descriptorsen
dc.subjectIntegral imageen
dc.titleGauge-SURF descriptorsen
dc.typeinfo:eu-repo/semantics/articleen
dc.subject.ecienciaElectrónicaes_ES
dc.subject.ecienciaElectronicsen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Electrónicaes_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.imavis.2012.11.001
dc.type.versioninfo:eu-repo/semantics/submittedVersionen
dc.identifier.doi10.1016/j.imavis.2012.11.001
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.publicationtitleImage and Vision Computing
dc.identifier.publicationvolume31
dc.identifier.publicationlastpage116
dc.identifier.publicationissue1
dc.identifier.publicationfirstpage103


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