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Optimizing visual dictionaries for effective image retrieval

Content Provider	Springer Nature Link
Author	Govindan, V. K. Arun, K. S.
Copyright Year	2015
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.
Starting Page	165
Ending Page	185
Page Count	21
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	4
Issue Number	3
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2015-02-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Visual dictionary Image retrieval Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Matrix factorization Information Systems Applications (incl. Internet) Multimedia Information Systems Sparse coding
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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