Towards a comprehensive survey of the semantic gap in visual image retrieval

Enser, Peter G.B. and Sandom, Christine J. (2003) Towards a comprehensive survey of the semantic gap in visual image retrieval In: Image and video retrieval. Lecture notes in computer science, 2728/2003 . Springer-Verlag, Berlin, Germany, pp. 291-299. ISBN 3540406344

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Abstract

This paper adopts the premise that the 'semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which this deficiency might be made good. Simple classifications of types of image and of types of user are proposed. Consideration is then given in outline to how semantic content is realised by each class of user within each class of image. The argument is advanced that this realisation finds expression in perceptual, generic interpretive and specific interpretive content. This analytic framework provides the basis for the specification of a broadly encompassing evaluation study, which will employ the image/user type classification and the expert domain knowledge of selected user groups in the construction of segmented test collections of real queries, images and relevance judgements. From this study should come a better-informed view on the nature of semantic information need, and on the representation and recovery of semantic content across a broad spectrum of image retrieval activity.

Item Type:Chapter in book
Subjects:G000 Computing and Mathematical Sciences > G500 Information Systems
Faculties:Faculty of Science and Engineering > School of Computing, Engineering and Mathematics
Faculty of Science and Engineering > School of Computing, Engineering and Mathematics > Visual Image Retrieval
ID Code:1137
Deposited By:editor cmis
Deposited On:08 May 2007
Last Modified:10 May 2012 02:18

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