Reference : Incremental Indexing and Distributed Image Search using Shared Randomized Vocabularies
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/4319
Incremental Indexing and Distributed Image Search using Shared Randomized Vocabularies
English
Marée, Raphaël mailto [Université de Liège - ULg > > GIGA-Management : Plateforme bioinformatique >]
Denis, Philippe mailto [ > > ]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Mar-2010
ACM Proceedings MIR 2010
Yes
No
International
11th ACM SIGMM International Conference on Multimedia Information Retrieval
du 29 mars au 31 mars 2010
Philadelphia
USA
[en] content-based image retrieval ; incremental ; distributed
[fr] recherche d'images ; incrémentale ; distribuée
[en] We present a cooperative framework for content-based image retrieval
for the realistic setting where images are distributed across
multiple cooperating servers. The proposed
method is in line with bag-of-features approaches but uses fully
data-independent, randomized structures, shared by the cooperating
servers, to map image features to common visual words. A
coherent, global image similarity measure (which is a kernel) is computed in a distributed fashion over visual
words, by only requiring a small amount of data transfers between
nodes. Our experiments on various image types show that this framework
is a very promising step towards large-scale, distributed content-based image retrieval.
Fonds Européen de Développement Régional - FEDER ; Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS ; Politique Scientifique Fédérale (Belgique) = Belgian Federal Science Policy
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/4319
10.1145/1743384.1743405

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