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Global Pose Refinement using Bidirectional Long-Short Term Memory

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dc.contributor.authorRadwan, Ibrahim
dc.contributor.authorAsthana, Akshay
dc.contributor.authorGoecke, Roland
dc.coverage.spatialVenice, Italy
dc.date.accessioned2024-01-16T00:15:29Z
dc.date.createdOctober 22-29, 2017
dc.date.issued2017
dc.date.updated2022-09-25T08:17:36Z
dc.description.abstractIn This paper, a bi-directional long-short term memory (LSTM) framework is proposed to refine pose estimation and tracking for multiple people. The key idea of our algorithm is to learn the temporal consistencies of the human body shapes between subsequent frames. This helps removing the wrong sudden outliers and improve the general smoothness of the pose tracking. The proposed approach has been evaluated on PoseTrack dataset for both the validation and test subset sequences. The overall detection and tracking results have been improved over the frame-by-frame only baseline detection.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.urihttp://hdl.handle.net/1885/311470
dc.language.isoen_AUen_AU
dc.publisherIEEEen_AU
dc.relation.ispartofseriesIEEE International Conference on Computer Vision, PoseTrack Workshop and Challengeen_AU
dc.rights© 2017 IEEEen_AU
dc.titleGlobal Pose Refinement using Bidirectional Long-Short Term Memoryen_AU
dc.typeConference paperen_AU
local.bibliographicCitation.lastpage5en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationRadwan, Ibrahim, College of Business and Economics, ANUen_AU
local.contributor.affiliationAsthana, Akshay, Seeing Machines Ltden_AU
local.contributor.affiliationGoecke, Roland, University of Canberraen_AU
local.contributor.authoruidRadwan, Ibrahim, u1041716en_AU
local.description.embargo2099-12-31
local.description.notesImported from ARIESen_AU
local.description.refereedYes
local.identifier.absfor359999 - Other commerce, management, tourism and services not elsewhere classifieden_AU
local.identifier.ariespublicationu4868915xPUB143en_AU
local.publisher.urlhttps://www.ieee.org/en_AU
local.type.statusPublished Versionen_AU

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