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dc.contributor.authorMolina-Cabello, Miguel Angel
dc.contributor.authorLópez-Rubio, Ezequiel 
dc.contributor.authorLuque-Baena, Rafael Marcos
dc.contributor.authorDomínguez, Enrique
dc.contributor.authorPalomo, Esteban José
dc.date.accessioned2016-10-26T08:59:08Z
dc.date.available2016-10-26T08:59:08Z
dc.date.created2016
dc.identifier.urihttp://hdl.handle.net/10630/12284
dc.description.abstractAmong current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which uses a uniform distribution to represent the foreground. A suitable set of characteristic pixel features is chosen to train the probabilistic model. Our approach has been compared to some competing methods on a test set of benchmark videos, with favorable results.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectAlgoritmos computacionaleses_ES
dc.subject.otherForeground detectiones_ES
dc.subject.otherBackground modelinges_ES
dc.subject.otherProbabilistic self-organising mapses_ES
dc.subject.otherBackground featureses_ES
dc.titlePixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environmentses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleInternational Joint Conference SOCO’16-CISIS’16-ICEUTE’16es_ES
dc.relation.eventplaceSan Sebastian (Spain)es_ES
dc.relation.eventdateOctubre 2016es_ES
dc.cclicenseby-nc-ndes_ES


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