Recently, progressive retrieval has been advocated as an alternate solution to multidimensional indexes or approximate techniques, in order to accelerate similarity search of points in multidimensional spaces. The principle of progressive search is to offer a first subset of the answers to the user during retrieval. If this subset satisfies the user's needs retrieval stops. Otherwise search resumes, and after a number of steps the exact answer set is returned to the user. Such a process is justified by the fact that in a large number of applications it is more interesting to rapidly bring first approximate answer sets rather than waiting for a long time the exact answer set. The contribution of this paper is a first typology of existing techniques for progressive retrieval. We survey a variety of methods designed for image retrieval although some of them apply to a general database browsing context which goes beyond CBIR. We also include techniques not designed for but that can easily be adapted to progressive retrieval. © 2008 Springer.
CITATION STYLE
Bouteldja, N., Gouet-Brunet, V., & Scholl, M. (2008). The many facets of progressive retrieval for CBIR. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5353 LNCS, pp. 611–624). https://doi.org/10.1007/978-3-540-89796-5_63
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