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dc.contributor.authorBarahona, S.
dc.contributor.authorGual-Arnau, Ximo
dc.contributor.authorIbáñez Gual, Maria Victoria
dc.contributor.authorSimó Vidal, Amelia
dc.date.accessioned2018-10-15T09:44:09Z
dc.date.available2018-10-15T09:44:09Z
dc.date.issued2018-06
dc.identifier.citationBARAHONA, Sonia, et al. Unsupervised classification of children’s bodies using currents. Advances in Data Analysis and Classification, 2018, vol. 12, no 2, p. 365-397.ca_CA
dc.identifier.issn1862-5347
dc.identifier.issn1862-5355
dc.identifier.urihttp://hdl.handle.net/10234/176729
dc.description.abstractObject classification according to their shape and size is of key importance in many scientific fields. This work focuses on the case where the size and shape of an object is characterized by a current. A current is a mathematical object which has been proved relevant to the modeling of geometrical data, like submanifolds, through integration of vector fields along them. As a consequence of the choice of a vector-valued reproducing kernel Hilbert space (RKHS) as a test space for integrating manifolds, it is possible to consider that shapes are embedded in this Hilbert Space. A vector-valued RKHS is a Hilbert space of vector fields; therefore, it is possible to compute a mean of shapes, or to calculate a distance between two manifolds. This embedding enables us to consider size-and-shape clustering algorithms. These algorithms are applied to a 3D database obtained from an anthropometric survey of the Spanish child population with a potential application to online sales of children’s wear.ca_CA
dc.format.extent33 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringer Verlagca_CA
dc.relation.isPartOfAdvances in Data Analysis and Classification, 2018, vol. 12, no 2ca_CA
dc.rights© Springer-Verlag Berlin Heidelbergca_CA
dc.subjectcurrentsca_CA
dc.subjectstatistical shape analysisca_CA
dc.subjectreproducing kernel Hilbert spaceca_CA
dc.subjectchildren's body shapesca_CA
dc.subjectk-Meansca_CA
dc.titleUnsupervised classification of children’s bodies using currentsca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1007/s11634-017-0283-0
dc.relation.projectIDSpanish Ministry of Science and Innovation: DPI2013 - 47279 - C2 -1 - Rca_CA
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://link.springer.com/article/10.1007/s11634-017-0283-0ca_CA
dc.contributor.funderWe would also like to thank the Valencian Institute of Biomechanics for providing us with the data set. S.ca_CA
dc.type.versioninfo:eu-repo/semantics/submittedVersionca_CA


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