Semantic indexing of multimedia content using textual and visual information

dc.citation.epage194
dc.citation.issue2/3fr_FR
dc.citation.spage182
dc.citation.volume5fr_FR
dc.contributor.authorAmrane, Abdesalam
dc.contributor.authorMellah, Hakima
dc.contributor.authorAmghar, Youssef
dc.contributor.authorAliradi, Rachid
dc.date.accessioned2013-12-08T16:11:30Z
dc.date.available2013-12-08T16:11:30Z
dc.date.issued2014
dc.description.abstractThe challenge in multimedia information retrieval remains in the indexing process, an active search area. There are three fundamental techniques for indexing multimedia content: those using textual information, and those using low-level information and those that combine different information extracted from multimedia. Each approach has its advantages and disadvantages as well to improve multimedia retrieval systems. The recent works are oriented towards multimodal approaches. In this paper we propose an approach that combines the surrounding text with the information extracted from the visual content of multimedia and represented in the same repository in order to allow querying multimedia content based on keywords or concepts. Each word contained in queries or in description of multimedia is disambiguated using the WordNet ontology in order to define its semantic concept. Support Vector Machines (SVMs) are used for image classification in one of the defined semantic concept based on SIFT (Scale Invariant Feature Transform) descriptors.fr_FR
dc.identifier.doi10.1504/IJAMC.2014.060496
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/470
dc.publisherIndersciencefr_FR
dc.relation.ispartofInternational Journal of Advanced Media and Communication (IJAMC)fr_FR
dc.rights.holderIndersciencefr_FR
dc.structureTechnologies des Systèmes Web et Multimédia et de Gestion de Contenufr_FR
dc.structureRecherche, Filtrage et Traitement Automatique de l'Informationfr_FR
dc.subjectmultimedia retrieval; automatic annotation; semantic representation; multimodal image representation; SVM; SIFT; textual querying.fr_FR
dc.titleSemantic indexing of multimedia content using textual and visual informationfr_FR
dc.typeArticle
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