Semantic image retrieval system based on object relationships

dc.contributor.authorShivakumar, S.
dc.contributor.authorGoel, N.
dc.contributor.authorAnanthanarayana, V.S.
dc.contributor.authorCyriac, C.
dc.contributor.authorRajaram, P.
dc.date.accessioned2026-02-06T06:40:02Z
dc.date.issued2013
dc.description.abstractSemantic-based image retrieval has recently become popular as an avenue to improve retrieval accuracy. The 'semantic gap' between the visual features and the high-level semantic features could be narrowed down by utilizing this kind of retrieval method. However, most of the current methods of semantic-based image retrieval utilize visual semantic features and do not consider spatial relationships. We build a system for content-based image retrieval from image collections on the web and tackle the challenges of distinguishing between images that contain similar objects, in order to capture the semantic meaning of a search query. In order to do so, we utilize a combination of segmentation into objects as well as the relationships of these objects with each other. © 2013 IEEE.
dc.identifier.citation2013 IEEE 2nd International Conference on Image Information Processing, IEEE ICIIP 2013, 2013, Vol., , p. 276-281
dc.identifier.urihttps://doi.org/10.1109/ICIIP.2013.6707598
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32681
dc.subjectimage segmentation
dc.subjectScale Invariant Feature Transform (SIFT)
dc.subjectsemantic gap
dc.subjectSemantic image retrieval
dc.titleSemantic image retrieval system based on object relationships

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