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dc.contributor.authorAlqasrawi, Yousef T. N.
dc.contributor.authorNeagu, Daniel
dc.date.accessioned2016-11-23T18:22:08Z
dc.date.available2016-11-23T18:22:08Z
dc.date.issued2014
dc.identifier.citationAlqasrawi Y and Neagu D (2014) Investigating the relationship between the distribution of local semantic concepts and local keypoints for image annotation. In: 14th UK Workshop on Computational Intelligence (UKCI). 8-10 Sep 2014, Bradford, UK: 1-7.
dc.identifier.urihttp://hdl.handle.net/10454/10580
dc.descriptionYes
dc.description.abstractThe problem of image annotation has gained increasing attention from many researchers in computer vision. Few works have addressed the use of bag of visual words for scene annotation at region level. The aim of this paper is to study the relationship between the distribution of local semantic concepts and local keypoints located in image regions labelled with these semantic concepts. Based on this study, we investigate whether bag of visual words model can be used to efficiently represent the content of natural scene image regions, so images can be annotated with local semantic concepts. Also, this paper presents local from global approach which study the influence of using visual vocabularies generated from general scene categories to build bag of visual words at region level. Extensive experiments are conducted over a natural scene dataset with six categories. The reported results have shown the plausibility of using the BOW model to represent the semantic information of image regions.
dc.relation.isreferencedbyhttps://doi.org/10.1109/UKCI.2014.6930165
dc.subjectConcept-based bag of visual words; Scene image annotation; Semantic modelling; Visual vocabulary
dc.titleInvestigating the relationship between the distribution of local semantic concepts and local keypoints for image annotation
dc.status.refereedNo
dc.typeConference Paper
dc.type.versionNo full-text available in the repository


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