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Bayesian human motion intentionality prediction in urban environments
dc.contributor.author | Ferrer Mínguez, Gonzalo |
dc.contributor.author | Sanfeliu Cortés, Alberto |
dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2015-03-13T15:38:27Z |
dc.date.available | 2015-03-13T15:38:27Z |
dc.date.created | 2014-07-15 |
dc.date.issued | 2014-07-15 |
dc.identifier.citation | Ferrer, G.; Sanfeliu, A. Bayesian human motion intentionality prediction in urban environments. "Pattern recognition letters", 15 Juliol 2014, vol. 44, p. 134-140. |
dc.identifier.issn | 0167-8655 |
dc.identifier.uri | http://hdl.handle.net/2117/26703 |
dc.description.abstract | Human 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.extent | 7 p. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Robòtica |
dc.subject.other | Human motion prediction |
dc.subject.other | Pattern recognition |
dc.subject.other | Crowd analysis |
dc.subject.other | PEOPLE |
dc.subject.other | NAVIGATION |
dc.subject.other | ROBOTS |
dc.title | Bayesian human motion intentionality prediction in urban environments |
dc.type | Article |
dc.contributor.group | Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents |
dc.identifier.doi | 10.1016/j.patrec.2013.08.013 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.inspec | Classificació INSPEC::Pattern recognition |
dc.rights.access | Open Access |
local.identifier.drac | 12891340 |
dc.description.version | Postprint (published version) |
local.citation.author | Ferrer, G.; Sanfeliu, A. |
local.citation.publicationName | Pattern recognition letters |
local.citation.volume | 44 |
local.citation.startingPage | 134 |
local.citation.endingPage | 140 |
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