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dc.contributor.authorLin, Xiao
dc.contributor.authorCasas Pla, Josep Ramon
dc.contributor.authorPardàs Feliu, Montse
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2017-02-16T12:08:27Z
dc.date.available2017-11-24T01:30:52Z
dc.date.issued2016-11-24
dc.identifier.citationLin, X., Casas, J., Pardas, M. 3D point cloud video segmentation based on interaction analysis. A: "Computer Vision – ECCV 2016 Workshops". Berlín: Springer, 2016, p. 821-835.
dc.identifier.isbn978-3-319-49408-1
dc.identifier.urihttp://hdl.handle.net/2117/101141
dc.description.abstractGiven the widespread availability of point cloud data from consumer depth sensors, 3D segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It benefits from the richer information contained in actual world 3D data compared to apparent (projected) data in 2D images. This also implies that the classical color segmentation challenges have recently shifted to RGBD data, whereas new emerging challenges are added as 3D information from depth measurements is usually noisy, sparse and unorganized. We present a novel segmentation approach for 3D point cloud video based on low level features and oriented to the analysis of object interactions. A hierarchical representation of the input point cloud is proposed to efficiently segment 3D data at the finer level, and to temporally establish the correspondence between segments, while dynamically managing the object split and merge at the coarser level. Experiments illustrate promising results and its potential application in object interaction analysis.
dc.format.extent15 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors::Internet
dc.subject.lcshCloud computing
dc.subject.lcshThree-dimensional imaging
dc.subject.otherObject segmentation
dc.subject.other3d point clouds
dc.subject.otherDynamic split and merge management
dc.subject.otherObject interactions
dc.title3D point cloud video segmentation based on interaction analysis
dc.typePart of book or chapter of book
dc.subject.lemacComputació en núvol
dc.subject.lemacImatges tridimensionals
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.identifier.doi10.1007/978-3-319-49409-8
dc.relation.publisherversionhttp://link.springer.com/book/10.1007%2F978-3-319-49409-8
dc.rights.accessOpen Access
local.identifier.drac19706108
dc.description.versionPostprint (author's final draft)
local.citation.authorLin, X.; Casas, J.; Pardas, M.
local.citation.pubplaceBerlín
local.citation.publicationNameComputer Vision – ECCV 2016 Workshops
local.citation.startingPage821
local.citation.endingPage835


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