@InProceedings{Mar{\c c}alRusi{\~n}ol2011,
author="Mar{\c{c}}al Rusi{\~n}ol
and David Aldavert
and Dimosthenis Karatzas
and Ricardo Toledo
and Josep Llados",
editor="P. Clough
and C. Foley
and C. Gurrin
and G.J.F. Jones
and W. Kraaij
and H. Lee
and V. Murdoch",
title="Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval",
booktitle="33rd European Conference on Information Retrieval",
year="2011",
publisher="Springer",
address="Berlin",
volume="6611",
pages="314--325",
abstract="In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices{\textquoteright} digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.",
optnote="DAG; RV;ADAS",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1737), last updated on Thu, 17 May 2012 10:11:05 +0200",
isbn="978-3-642-20160-8",
doi="10.1007/978-3-642-20161-5_32"
}