%0 Conference Proceedings
%T Integrating Visual and Textual Cues for Query-by-String Word Spotting
%A David Aldavert
%A Marçal Rusiñol
%A Ricardo Toledo
%A Josep Llados
%B 12th International Conference on Document Analysis and Recognition
%D 2013
%@ 1520-5363
%F David Aldavert2013
%O DAG; ADAS; 600.045; 600.055; 600.061
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2224), last updated on Thu, 10 Nov 2016 12:07:17 +0100
%X In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.
%U http://refbase.cvc.uab.es/files/ART2013.pdf
%U http://dx.doi.org/10.1109/ICDAR.2013.108
%P 511-515