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dc.contributor.authorFerrer Mínguez, Gonzalo
dc.contributor.authorSanfeliu Cortés, Alberto
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2015-03-13T15:38:27Z
dc.date.available2015-03-13T15:38:27Z
dc.date.created2014-07-15
dc.date.issued2014-07-15
dc.identifier.citationFerrer, G.; Sanfeliu, A. Bayesian human motion intentionality prediction in urban environments. "Pattern recognition letters", 15 Juliol 2014, vol. 44, p. 134-140.
dc.identifier.issn0167-8655
dc.identifier.urihttp://hdl.handle.net/2117/26703
dc.description.abstractHuman motion prediction in indoor and outdoor scenarios is a key issue towards human robot interaction and intelligent robot navigation in general. In the present work, we propose a new human motion intentionality indicator, denominated Bayesian Human Motion Intentionality Prediction (BHMIP), which is a geometric-based long-term predictor. Two variants of the Bayesian approach are proposed, the Sliding Window BHMIP and the Time Decay BHMIP. The main advantages of the proposed methods are: a simple formulation, easily scalable, portability to unknown environments with small learning effort, low computational complexity, and they outperform other state of the art approaches. The system only requires training to obtain the set of destinations, which are salient positions people normally walk to, that configure a scene. A comparison of the BHMIP is done with other well known methods for long-term prediction using the Edinburgh Informatics Forum pedestrian database and the Freiburg People Tracker database. (C) 2013 Elsevier B.V. All rights reserved.
dc.format.extent7 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject.otherHuman motion prediction
dc.subject.otherPattern recognition
dc.subject.otherCrowd analysis
dc.subject.otherPEOPLE
dc.subject.otherNAVIGATION
dc.subject.otherROBOTS
dc.titleBayesian human motion intentionality prediction in urban environments
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents
dc.identifier.doi10.1016/j.patrec.2013.08.013
dc.description.peerreviewedPeer Reviewed
dc.subject.inspecClassificació INSPEC::Pattern recognition
dc.rights.accessOpen Access
local.identifier.drac12891340
dc.description.versionPostprint (published version)
local.citation.authorFerrer, G.; Sanfeliu, A.
local.citation.publicationNamePattern recognition letters
local.citation.volume44
local.citation.startingPage134
local.citation.endingPage140


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain