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dc.contributor.authorGomez-Ojeda, Ruben
dc.contributor.authorMoreno, Francisco-Angel
dc.contributor.authorGonzalez-Jimenez, Antonio Javier 
dc.date.accessioned2017-07-26T07:33:02Z
dc.date.available2017-07-26T07:33:02Z
dc.date.created2017
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10630/14376
dc.description.abstractPoint-based stereo visual odometry systems typically estimate the camera motion by minimizing a cost function of the projection residuals between consecutive frames. Under some mild assumptions, such minimization is equivalent to maximizing the probability of the measured residuals given a certain pose change, for which a suitable model of the error distribution (sensor model) becomes of capital importance in order to obtain accurate results. This paper proposes a robust probabilistic model for projection errors, based on real world data. For that, we argue that projection distances follow Gamma distributions, and hence, the introduction of these models in a probabilistic formulation of the motion estimation process increases both precision and accuracy. Our approach has been validated through a series of experiments with both synthetic and real data, revealing an improvement in accuracy while not increasing the computational burden.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Project "PROMOVE: Advances in mobile robotics for promoting independent life of elders", funded by the Spanish Government and the "European Regional Development Fund ERDF" under contract DPI2014-55826-R.es_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectCampo visuales_ES
dc.subject.othervisual odometryes_ES
dc.subject.otherSLAMes_ES
dc.subject.otherStereo visiones_ES
dc.titleAccurate Stereo Visual Odometry with Gamma Distributionses_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleIEEE International Conference on Robotics and Automation (ICRA)es_ES
dc.relation.eventplaceSingaporees_ES
dc.relation.eventdateMay, 2017es_ES
dc.identifier.orcidhttp://orcid.org/0000-0003-3845-3497es_ES
dc.cclicenseby-nc-ndes_ES


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