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Consistent depth video segmentation using adaptive surface models
dc.contributor.author | Husain, Syed Farzad |
dc.contributor.author | Dellen, Babette |
dc.contributor.author | Torras, Carme |
dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
dc.date.accessioned | 2015-06-30T18:21:56Z |
dc.date.available | 2015-06-30T18:21:56Z |
dc.date.created | 2014 |
dc.date.issued | 2014 |
dc.identifier.citation | Husain, S.; Dellen, B.; Torras, C. Consistent depth video segmentation using adaptive surface models. "IEEE Transactions on Cybernetics", 2014, vol. 45, núm. 2, p. 266-278. |
dc.identifier.issn | 2168-2267 |
dc.identifier.uri | http://hdl.handle.net/2117/28476 |
dc.description.abstract | We propose a new approach for the segmentation of 3-D point clouds into geometric surfaces using adaptive surface models. Starting from an initial configuration, the algorithm converges to a stable segmentation through a new iterative split-and-merge procedure, which includes an adaptive mechanism for the creation and removal of segments. This allows the segmentation to adjust to changing input data along the movie, leading to stable, temporally coherent, and traceable segments. We tested the method on a large variety of data acquired with different range imaging devices, including a structured-light sensor and a time-of-flight camera, and successfully segmented the videos into surface segments. We further demonstrated the feasibility of the approach using quantitative evaluations based on ground-truth data. |
dc.format.extent | 13 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 | computer vision |
dc.subject.other | motion |
dc.subject.other | range data |
dc.subject.other | segmentation |
dc.subject.other | shape |
dc.subject.other | surface fitting |
dc.title | Consistent depth video segmentation using adaptive surface models |
dc.type | Article |
dc.contributor.group | Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI |
dc.identifier.doi | 10.1109/TCYB.2014.2324815 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.inspec | Classificació INSPEC::Pattern recognition::Computer vision |
dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6824182 |
dc.rights.access | Open Access |
local.identifier.drac | 15436253 |
dc.description.version | Postprint (author’s final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/FP7/269959/EU/Intelligent observation and execution of Actions and manipulations/INTELLACT |
local.citation.author | Husain, S.; Dellen, B.; Torras, C. |
local.citation.publicationName | IEEE Transactions on Cybernetics |
local.citation.volume | 45 |
local.citation.number | 2 |
local.citation.startingPage | 266 |
local.citation.endingPage | 278 |
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