Abstract
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.
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Bouteldja, N., Gouet-Brunet, V., Scholl, M. (2008). The Many Facets of Progressive Retrieval for CBIR. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_63
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DOI: https://doi.org/10.1007/978-3-540-89796-5_63
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