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Title: Image similarity retrieval by spatial constraints
Authors: Papadias, Dimitris
Mamoulis, Nikos
Meretakis, Dimitris
Keywords: Spatial constraints
Image similarity retrieval
Issue Date: 1998
Citation: Proceedings of the 7th ACM Conference on Information and Knowledge Management (CIKM), Washington DC, ACM Press, 1998
Abstract: This paper deals with queries involving the retrieval of images that contain certain object configurations. Consider, for instance, that a user wants to "find all images where there exists a building adjacent to the west side of a park which southwest and near a commercial center". This query can be formulated as a constraint satisfaction problem (CSP) where the query variables are nodes of the corresponding constraint network and the image objects constitute the domain of each variable. The arcs of the network correspond to spatial constraints (e.g., adjacent west (X1,X2), southwest near (X2,X3)). Problems of the above nature are, in general, intractable. In addition, spatial constraints (e.g., southwest, near) lack universally accepted semantics and cannot always be modeled by crisp relations; a fact that further complicates query processing. This paper focuses on the development of effective methods that take advantage of the special structure of the spatial domain to achieve good average performance even for large images and queries.
Rights: © ACM, 1998. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 7th ACM Conference on Information and Knowledge Management (CIKM), Washington DC, ACM Press, 1998
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