A framework for high level semantic annotation using trusted object annotated dataset

Irfanullah and Aslam, N. and Loo, J. and Loomes, M. and Roohullah (2010) A framework for high level semantic annotation using trusted object annotated dataset. In: UNSPECIFIED.

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Abstract

Dramatic expansion and eminence of the multimedia data from the last decades, culminates to a trouble in managing, accessing and annotating the data. The high level semantic annotation (HLS) of resources in general and multimedia resources in particular, is a resilient job. The Progression in automatic annotation mechanisms have not been able to comprehend with adequately accurate results. To outfit multimedia (e.g. image/video) retrieval capabilities, digital libraries have hung on manual annotation of images. Providing a track to enact high level semantic annotation automatically would be more worthwhile, efficient and scalable with magnifying image collections. This paper intent to equip the high level semantic annotation for images, and consequently, contributes to 1) calculating semantic intensity (SI) of each object in the image depicting the dominancy factor, (2) image similarity on the bases on metadata tag with the images, and (3) clustering approach based on the image similarity to tag set of images with a high level semantic description with their calculated similarity values. The experiment on a portion of randomly selected images from LabelMe database manifests stimulating outcomes. © 2011 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0
Uncontrolled Keywords: Digital libraries; Image analysis; Image annotation; Multimedia systems, Automatic annotation; Clustering approach; High level semantics; Image collections; Image similarity; Manual annotation; Multimedia resources; Semantic intensity, Semantics
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:49
Last Modified: 09 Nov 2023 15:49
URI: https://khub.utp.edu.my/scholars/id/eprint/1342

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