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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/44934
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dc.contributor.authorFlint, A.-
dc.contributor.authorDick, A.-
dc.contributor.authorVan Den Hengel, A.-
dc.contributor.editorBottema, M.-
dc.date.issued2007-
dc.identifier.citationProceedings of DICTA 2007 / pp.182-188-
dc.identifier.isbn0769530672-
dc.identifier.isbn9780769530673-
dc.identifier.urihttp://hdl.handle.net/2440/44934-
dc.description.abstractThis paper presents a method for describing and recognising local structure in 3D images. The method extends proven techniques for 2D object recognition in images. In particular, we propose a 3D interest point detector that is based on SURF, and a 3D descriptor that extends SIFT. The method is applied to the problem of detecting repeated structure in range images, and promising results are reported.-
dc.description.statementofresponsibilityFlint, Alex; Dick, A.; Hengel, Anton Van Den-
dc.language.isoen-
dc.publisherIEEE-
dc.rights© 2008 IEEE – All Rights Reserved-
dc.source.urihttp://dx.doi.org/10.1109/dicta.2007.4426794-
dc.titleThrift: Local 3D structure recognition-
dc.typeConference paper-
dc.contributor.conferenceBiennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (9th : 2007 : Glenelg, Australia)-
dc.identifier.doi10.1109/DICTA.2007.4426794-
dc.publisher.placeCDROM-
pubs.publication-statusPublished-
dc.identifier.orcidDick, A. [0000-0001-9049-7345]-
dc.identifier.orcidVan Den Hengel, A. [0000-0003-3027-8364]-
Appears in Collections:Aurora harvest 6
Computer Science publications

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