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Human motion capture using scalable body models
dc.contributor.author | Canton Ferrer, Cristian |
dc.contributor.author | Casas Pla, Josep Ramon |
dc.contributor.author | Pardàs Feliu, Montse |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2011-09-29T16:45:32Z |
dc.date.available | 2011-09-29T16:45:32Z |
dc.date.created | 2011-10 |
dc.date.issued | 2011-10 |
dc.identifier.citation | Canton-Ferrer, C.; Casas, J.; Pardas, M. Human motion capture using scalable body models. "Computer vision and image understanding", Octubre 2011, vol. 115, núm. 10, p. 1363-1374. |
dc.identifier.issn | 1077-3142 |
dc.identifier.uri | http://hdl.handle.net/2117/13393 |
dc.description.abstract | This paper presents a general analysis framework towards exploiting the underlying hierarchical and scalable structure of an articulated object for pose estimation and tracking. Scalable human body models are introduced as an ordered set of articulated models fulfilling an inclusive hierarchy. The concept of annealing is applied to derive a generic particle filtering scheme able to perform a sequential filtering over the set of models contained in the scalable human body model. Two annealing loops are employed, the standard likelihood annealing and the newly introduced structural annealing, leading to a robust, progressive and efficient analysis of the input data. The validity of this scheme is tested by performing markerless human motion capture in a multi-camera environment employing the standard HumanEva annotated datasets. Finally, quantitative results are presented and compared with other existing HMC techniques. |
dc.format.extent | 12 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::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radiodifusió per televisió |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo |
dc.subject.lcsh | Motion Capturing |
dc.title | Human motion capture using scalable body models |
dc.type | Article |
dc.subject.lemac | Imatges -- Processament -- Tècniques digitals |
dc.subject.lemac | Imatges tridimensionals |
dc.contributor.group | Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
dc.identifier.doi | 10.1016/j.cviu.2011.06.001 |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 5963643 |
dc.description.version | Postprint (published version) |
local.citation.author | Canton-Ferrer, C.; Casas, J.; Pardas, M. |
local.citation.publicationName | Computer vision and image understanding |
local.citation.volume | 115 |
local.citation.number | 10 |
local.citation.startingPage | 1363 |
local.citation.endingPage | 1374 |
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