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Describing the where – improving image annotation and search through geography


Purves, Ross S; Edwardes, Alistair; Sanderson, Mark (2008). Describing the where – improving image annotation and search through geography. In: Csurka, G. Proceedings of the workshop on Metadata Mining for Image Understanding (MMIU 2008). Setúbal: Insticc Press, 105-113.

Abstract

Image retrieval, using either content or text-based techniques, does not match up to the current quality of standard text retrieval. One possible reason for this mismatch is the semantic gap – the terms by which images are indexed do not accord with those imagined by users querying image databases. In this paper we set out to describe how geography might help to index the where facet of the Pansofsky-Shatford matrix, which has previously been shown to accord well with the types of queries users make. We illustrate these ideas with existing (e.g. identifying place names associated with a set of coordinates) and novel (e.g. describing images using land cover data) techniques to describe images and contend that such methods will become
central as increasing numbers of images become georeferenced.

Abstract

Image retrieval, using either content or text-based techniques, does not match up to the current quality of standard text retrieval. One possible reason for this mismatch is the semantic gap – the terms by which images are indexed do not accord with those imagined by users querying image databases. In this paper we set out to describe how geography might help to index the where facet of the Pansofsky-Shatford matrix, which has previously been shown to accord well with the types of queries users make. We illustrate these ideas with existing (e.g. identifying place names associated with a set of coordinates) and novel (e.g. describing images using land cover data) techniques to describe images and contend that such methods will become
central as increasing numbers of images become georeferenced.

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2 citations in Web of Science®
18 citations in Scopus®
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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Software
Language:English
Date:2008
Deposited On:07 Jan 2009 09:25
Last Modified:02 Nov 2023 02:38
Publisher:Insticc Press
Additional Information:3rd International Conference on Computer Vision Theory and Applications, 22-25 January, 2008,Funchal, Madeira (Portugal)
OA Status:Green
Official URL:http://www.visapp.org/VISAPP2008/
  • Content: Accepted Version