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dc.contributor.authorSimó Serra, Edgar
dc.contributor.authorQuattoni, Ariadna Julieta
dc.contributor.authorTorras, Carme
dc.contributor.authorMoreno-Noguer, Francesc
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2013-12-10T10:35:59Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationSimo, E. [et al.]. A joint model for 2D and 3D pose estimation from a single image. A: IEEE Conference on Computer Vision and Pattern Recognition. "Proceedings : 2013 IEEE Conference on Computer Vision and Pattern Recognition : CVPR 2013". Portland, Oregon: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 3634-3641.
dc.identifier.urihttp://hdl.handle.net/2117/20946
dc.description.abstractWe introduce a novel approach to automatically recover 3D human pose from a single image. Most previous work follows a pipelined approach: initially, a set of 2D features such as edges, joints or silhouettes are detected in the image, and then these observations are used to infer the 3D pose. Solving these two problems separately may lead to erroneous 3D poses when the feature detector has performed poorly. In this paper, we address this issue by jointly solving both the 2D detection and the 3D inference problems. For this purpose, we propose a Bayesian framework that integrates a generative model based on latent variables and discriminative 2D part detectors based on HOGs, and perform inference using evolutionary algorithms. Real experimentation demonstrates competitive results, and the ability of our methodology to provide accurate 2D and 3D pose estimations even when the 2D detectors are inaccurate.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshComputer vision -- Mathematical models
dc.subject.otherDeformable models
dc.subject.otherDetectors
dc.subject.otherEstimation
dc.subject.otherJoints
dc.subject.otherShape
dc.subject.otherSolid modeling
dc.subject.otherThree-dimensional displays
dc.titleA joint model for 2D and 3D pose estimation from a single image
dc.typeConference report
dc.subject.lemacVisió per ordinador -- Models matemàtics
dc.contributor.groupUniversitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents
dc.contributor.groupUniversitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge
dc.identifier.doi10.1109/CVPR.2013.466
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6619310
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac12912706
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MICINN/6PN/DPI2011-27510
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/269959/EU/Intelligent observation and execution of Actions and manipulations/INTELLACT
dc.date.lift10000-01-01
local.citation.authorSimo, E.; Quattoni, A.J.; Torras, C.; Moreno-Noguer, F.
local.citation.contributorIEEE Conference on Computer Vision and Pattern Recognition
local.citation.pubplacePortland, Oregon
local.citation.publicationNameProceedings : 2013 IEEE Conference on Computer Vision and Pattern Recognition : CVPR 2013
local.citation.startingPage3634
local.citation.endingPage3641


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