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International Journal of Multimedia Information Retrieval
Published in: International Journal of Multimedia Information Retrieval 3/2015

01-09-2015 | Regular Paper

Optimizing visual dictionaries for effective image retrieval

Authors: K. S. Arun, V. K. Govindan

Published in: International Journal of Multimedia Information Retrieval | Issue 3/2015

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Abstract

Characterizing images by high-level concepts from a learned visual dictionary is extensively used in image classification and retrieval. This paper deals with inferring discriminative visual dictionaries for effective image retrieval and examines a non-negative visual dictionary learning scheme towards this direction. More specifically, a non-negative matrix factorization framework with \(\ell _0\)-sparseness constraint on the coefficient matrix for optimizing the dictionary is proposed. It is a two-step iterative process composed of sparse encoding and dictionary enhancement stages. An initial estimate of the visual dictionary is updated in each iteration with the proposed \(\ell _0\)-constraint gradient projection algorithm. A desirable attribute of this formulation is an adaptive sequential dictionary initialization procedure. This leads to a sharp drop down of the approximation error and a faster convergence. Finally, the proposed dictionary optimization scheme is used to derive a compact image representation for the retrieval task. A new image signature is obtained by projecting local descriptors on to the basis elements of the optimized visual dictionary and then aggregating the resulting sparse encodings in to a single feature vector. Experimental results on various benchmark datasets show that the proposed system can infer enhanced visual dictionaries and the derived image feature vector can achieve better retrieval results as compared to state-of-the-art techniques.
next article The influence of image descriptors’ dimensions’ value cardinalities on large-scale similarity search

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Metadata
Title
Optimizing visual dictionaries for effective image retrieval
Authors
K. S. Arun
V. K. Govindan
Publication date
01-09-2015
Publisher
Springer London
Published in
International Journal of Multimedia Information Retrieval / Issue 3/2015
Print ISSN: 2192-6611
Electronic ISSN: 2192-662X
DOI
https://doi.org/10.1007/s13735-015-0076-1

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