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Using PCL Gobal Descriptors in a DenseFusion Architecture

dc.contributor.authorPereira, Nuno
dc.contributor.authorAlexandre, Luís
dc.date.accessioned2020-01-09T11:56:12Z
dc.date.available2020-01-09T11:56:12Z
dc.date.issued2019-10
dc.description.abstractIn this paper, we present an alternative architecture to the state-of-the-art in 6D pose - DenseFusion. We changed the architecture of the method in the depth feature extraction phase. Instead of using the PointNet, as used in the original DenseFusion, we used global descriptors from the Point Cloud Library (PCL) to extract features. We made a comparison in terms of average accuracy between the Ensemble of Shape Functions (ESF), Viewpoint Feature Histogram (VHF) and the original PointNet.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8156
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.titleUsing PCL Gobal Descriptors in a DenseFusion Architecturept_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.title25th Portuguese Conference on Pattern Recognition (RECPAD 2019)pt_PT
person.familyNameAlexandre
person.givenNameLuís
person.identifier.ciencia-id2014-0F06-A3E3
person.identifier.orcid0000-0002-5133-5025
person.identifier.ridE-8770-2013
person.identifier.scopus-author-id8847713100
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication131ec6eb-b61a-4f27-953f-12e948a43a96
relation.isAuthorOfPublication.latestForDiscovery131ec6eb-b61a-4f27-953f-12e948a43a96

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