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dc.contributor.authorDetyniecki, Marcin
dc.contributor.authorMarsala, Christophe
dc.date.accessioned2013-04-10T17:25:54Z
dc.date.available2013-04-10T17:25:54Z
dc.date.issued2008
dc.identifier.citationDetyniecki, Marcin; Marsala, Christophe. Automatic video annotation with forests of fuzzy decision trees. "Mathware & Soft Computing", vol. 15, núm. 1, p. 61-74.
dc.identifier.issn1134-5632
dc.identifier.urihttp://hdl.handle.net/2099/13165
dc.description.abstractNowadays, the annotation of videos with high-level semantic concepts or features is a great challenge. In this paper, this problem is tackled by learning, by means of Fuzzy Decision Trees (FDT), automatic rules based on a limited set of examples. Rules intended, in an exploitation step, to reduce the need of human usage in the process of indexation. However, when addressing large, unbalanced, multiclass example sets, a single classi er - such as the FDT - is insu cient. Therefore we introduce the use of forests of fuzzy decision trees (FFDT) and we highlight: (a) its e ectiveness on a high level feature detection task, compared to other competitive systems and (b) the e ect on performance from the number of classi ers point of view. Moreover, since the resulting indexes are, by their nature, to be used in a retrieval application, we discuss the results under the lights of a ranking (vs. a classi cation) context.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.relation.ispartofMathware & Soft Computing. 2008, vol. 15, núm. 1
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teórica
dc.subject.lcshArtificial intelligence
dc.subject.otherVideo annotation
dc.subject.otherHigh level Features
dc.subject.otherForest of Fuzzy Decisions Trees
dc.titleAutomatic video annotation with forests of fuzzy decision trees
dc.typeArticle
dc.subject.lemacIntel•ligència artificial
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::68 Computer science::68T Artificial intelligence
dc.rights.accessOpen Access
upcommons.citation.authorDetyniecki, Marcin; Marsala, Christophe
upcommons.citation.publishedtrue
upcommons.citation.publicationNameMathware & Soft Computing
upcommons.citation.volume15
upcommons.citation.number1
upcommons.citation.startingPage61
upcommons.citation.endingPage74


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain