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Author Dimosthenis Karatzas; V. Poulain d'Andecy; Marçal Rusiñol edit   pdf
doi  openurl
  Title Human-Document Interaction – a new frontier for document image analysis Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 369-374  
  Keywords  
  Abstract All indications show that paper documents will not cede in favour of their digital counterparts, but will instead be used increasingly in conjunction with digital information. An open challenge is how to seamlessly link the physical with the digital – how to continue taking advantage of the important affordances of paper, without missing out on digital functionality. This paper
presents the authors’ experience with developing systems for Human-Document Interaction based on augmented document interfaces and examines new challenges and opportunities arising for the document image analysis field in this area. The system presented combines state of the art camera-based document
image analysis techniques with a range of complementary tech-nologies to offer fluid Human-Document Interaction. Both fixed and nomadic setups are discussed that have gone through user testing in real-life environments, and use cases are presented that span the spectrum from business to educational application
 
  Address Santorini; Greece; April 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.084; 600.077 Approved no  
  Call Number KPR2016 Serial 2756  
Permanent link to this record
 

 
Author Q. Bao; Marçal Rusiñol; M.Coustaty; Muhammad Muzzamil Luqman; C.D. Tran; Jean-Marc Ogier edit   pdf
doi  openurl
  Title Delaunay triangulation-based features for Camera-based document image retrieval system Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 1-6  
  Keywords Camera-based Document Image Retrieval; Delaunay Triangulation; Feature descriptors; Indexing  
  Abstract In this paper, we propose a new feature vector, named DElaunay TRIangulation-based Features (DETRIF), for real-time camera-based document image retrieval. DETRIF is computed based on the geometrical constraints from each pair of adjacency triangles in delaunay triangulation which is constructed from centroids of connected components. Besides, we employ a hashing-based indexing system in order to evaluate the performance of DETRIF and to compare it with other systems such as LLAH and SRIF. The experimentation is carried out on two datasets comprising of 400 heterogeneous-content complex linguistic map images (huge size, 9800 X 11768 pixels resolution)and 700 textual document images.  
  Address Santorini; Greece; April 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 600.084; 600.077 Approved no  
  Call Number Admin @ si @ BRC2016 Serial 2757  
Permanent link to this record
 

 
Author Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas edit   pdf
openurl 
  Title Dynamic Lexicon Generation for Natural Scene Images Type Conference Article
  Year 2016 Publication 14th European Conference on Computer Vision Workshops Abbreviated Journal  
  Volume Issue Pages 395-410  
  Keywords scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN  
  Abstract Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge bene t from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons
for scene images using only visual information. For this, we exploit
the correlation between visual and textual information in a dataset consisting
of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline.
 
  Address Amsterdam; The Netherlands; October 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECCVW  
  Notes DAG; 600.084 Approved no  
  Call Number Admin @ si @ PGR2016 Serial 2825  
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Author Fernando Vilariño; Dimosthenis Karatzas edit  openurl
  Title The Library Living Lab Type Conference Article
  Year 2015 Publication Open Living Lab Days Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Istanbul; Turkey; August 2015  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference OLLD  
  Notes MV; DAG;SIAI Approved no  
  Call Number Admin @ si @ViK2015 Serial 2797  
Permanent link to this record
 

 
Author Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel edit  openurl
  Title An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres Type Book Chapter
  Year 2015 Publication The White Book on Public Library Network from Diputació de Barcelona Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV; DAG;SIAI Approved no  
  Call Number Admin @ si @VKC2015 Serial 2798  
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Author Fernando Vilariño; Dimosthenis Karatzas edit  openurl
  Title A Living Lab approach for Citizen Science in Libraries Type Conference Article
  Year 2016 Publication 1st International ECSA Conference Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Berlin; Germany; May 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECSA  
  Notes MV; DAG; 600.084; 600.097;SIAI Approved no  
  Call Number Admin @ si @ViK2016 Serial 2804  
Permanent link to this record
 

 
Author Dena Bazazian; Raul Gomez; Anguelos Nicolaou; Lluis Gomez; Dimosthenis Karatzas; Andrew Bagdanov edit   pdf
openurl 
  Title Improving Text Proposals for Scene Images with Fully Convolutional Networks Type Conference Article
  Year 2016 Publication 23rd International Conference on Pattern Recognition Workshops Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Text Proposals have emerged as a class-dependent version of object proposals – efficient approaches to reduce the search space of possible text object locations in an image. Combined with strong word classifiers, text proposals currently yield top state of the art results in end-to-end scene text
recognition. In this paper we propose an improvement over the original Text Proposals algorithm of [1], combining it with Fully Convolutional Networks to improve the ranking of proposals. Results on the ICDAR RRC and the COCO-text datasets show superior performance over current state-of-the-art.
 
  Address Cancun; Mexico; December 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICPRW  
  Notes DAG; LAMP; 600.084 Approved no  
  Call Number Admin @ si @ BGN2016 Serial 2823  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
url  openurl
  Title A fast hierarchical method for multi‐script and arbitrary oriented scene text extraction Type Journal Article
  Year 2016 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 19 Issue 4 Pages 335-349  
  Keywords scene text; segmentation; detection; hierarchical grouping; perceptual organisation  
  Abstract Typography and layout lead to the hierarchical organisation of text in words, text lines, paragraphs. This inherent structure is a key property of text in any script and language, which has nonetheless been minimally leveraged by existing text detection methods. This paper addresses the problem of text
segmentation in natural scenes from a hierarchical perspective.
Contrary to existing methods, we make explicit use of text structure, aiming directly to the detection of region groupings corresponding to text within a hierarchy produced by an agglomerative similarity clustering process over individual regions. We propose an optimal way to construct such an hierarchy introducing a feature space designed to produce text group hypotheses with
high recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Results obtained over four standard datasets, covering text in variable orientations and different languages, demonstrate that our algorithm, while being trained in a single mixed dataset, outperforms state of the art
methods in unconstrained scenarios.
 
  Address  
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  Area Expedition Conference  
  Notes DAG; 600.056; 601.197 Approved no  
  Call Number Admin @ si @ GoK2016a Serial 2862  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
doi  openurl
  Title A fine-grained approach to scene text script identification Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 192-197  
  Keywords  
  Abstract This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online.  
  Address Santorini; Grecia; April 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DAS  
  Notes DAG; 601.197; 600.084 Approved no  
  Call Number Admin @ si @ GoK2016b Serial 2863  
Permanent link to this record
 

 
Author Youssef El Rhabi; Simon Loic; Brun Luc; Josep Llados; Felipe Lumbreras edit  doi
openurl 
  Title Information Theoretic Rotationwise Robust Binary Descriptor Learning Type Conference Article
  Year 2016 Publication Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) Abbreviated Journal  
  Volume Issue Pages 368-378  
  Keywords  
  Abstract In this paper, we propose a new data-driven approach for binary descriptor selection. In order to draw a clear analysis of common designs, we present a general information-theoretic selection paradigm. It encompasses several standard binary descriptor construction schemes, including a recent state-of-the-art one named BOLD. We pursue the same endeavor to increase the stability of the produced descriptors with respect to rotations. To achieve this goal, we have designed a novel offline selection criterion which is better adapted to the online matching procedure. The effectiveness of our approach is demonstrated on two standard datasets, where our descriptor is compared to BOLD and to several classical descriptors. In particular, it emerges that our approach can reproduce equivalent if not better performance as BOLD while relying on twice shorter descriptors. Such an improvement can be influential for real-time applications.  
  Address Mérida; Mexico; November 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (up)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference S+SSPR  
  Notes DAG; ADAS; 600.097; 600.086 Approved no  
  Call Number Admin @ si @ RLL2016 Serial 2871  
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