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Probabilistic Stereo Egomotion Transform

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dc.contributor.authorSilva, Hugo
dc.contributor.authorBernardino, A.
dc.contributor.authorSilva, Eduardo
dc.date.accessioned2015-12-14T11:49:55Z
dc.date.available2015-12-14T11:49:55Z
dc.date.issued2014
dc.description.abstractIn this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.pt_PT
dc.identifier.doi10.1109/ICRA.2014.6907662pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/7187
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relation.ispartofseriesICRA;2014
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6907662pt_PT
dc.subjectAngular velocitypt_PT
dc.subjectCameraspt_PT
dc.subjectEstimationpt_PT
dc.subjectProbabilistic logicpt_PT
dc.subjectRobot sensing systemspt_PT
dc.subjectVisualizationpt_PT
dc.titleProbabilistic Stereo Egomotion Transformpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceHong Kongpt_PT
oaire.citation.endPage5466pt_PT
oaire.citation.startPage5461pt_PT
oaire.citation.titleIEEE International Conference on Robotics and Automation (ICRA), 2014pt_PT
person.familyNameSilva
person.givenNameEduardo
person.identifier.ciencia-idC517-23DA-B09F
person.identifier.orcid0000-0001-7166-3459
person.identifier.ridM-7929-2014
person.identifier.scopus-author-id6507130721
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationd0912771-16c3-4f41-a936-79a714e984fb
relation.isAuthorOfPublication.latestForDiscoveryd0912771-16c3-4f41-a936-79a714e984fb

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