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Author Lluis Gomez; Y. Patel; Marçal Rusiñol; C.V. Jawahar; Dimosthenis Karatzas edit   pdf
url  doi
openurl 
  Title Self‐supervised learning of visual features through embedding images into text topic spaces Type Conference Article
  Year 2017 Publication 30th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages  
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  Abstract End-to-end training from scratch of current deep architectures for new computer vision problems would require Imagenet-scale datasets, and this is not always possible. In this paper we present a method that is able to take advantage of freely available multi-modal content to train computer vision algorithms without human supervision. We put forward the idea of performing self-supervised learning of visual features by mining a large scale corpus of multi-modal (text and image) documents. We show that discriminative visual features can be learnt efficiently by training a CNN to predict the semantic context in which a particular image is more probable to appear as an illustration. For this we leverage the hidden semantic structures discovered in the text corpus with a well-known topic modeling technique. Our experiments demonstrate state of the art performance in image classification, object detection, and multi-modal retrieval compared to recent self-supervised or natural-supervised approaches.  
  Address Honolulu; Hawaii; July 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVPR  
  Notes DAG; 600.084; 600.121 Approved no  
  Call Number Admin @ si @ GPR2017 Serial 2889  
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Author Marc Sunset Perez; Marc Comino Trinidad; Dimosthenis Karatzas; Antonio Chica Calaf; Pere Pau Vazquez Alcocer edit  url
openurl 
  Title Development of general‐purpose projection‐based augmented reality systems Type Journal
  Year 2016 Publication IADIs international journal on computer science and information systems Abbreviated Journal IADIs  
  Volume 11 Issue 2 Pages 1-18  
  Keywords  
  Abstract Despite the large amount of methods and applications of augmented reality, there is little homogenizatio n on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more co ncerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we describe the development of a software framework for AR setups. We concentrate on the modular design of the framework, but also on some hard problems such as the calibration stage, crucial for projection – based AR. The developed framework is suitable and has been tested in AR applications using camera – projector pairs, for both fixed and nomadic setups  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.084 Approved no  
  Call Number Admin @ si @ SCK2016 Serial 2890  
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Author Lluis Gomez edit  openurl
  Title Exploiting Similarity Hierarchies for Multi-script Scene Text Understanding Type Book Whole
  Year 2016 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Abstract This thesis addresses the problem of automatic scene text understanding in unconstrained conditions. In particular, we tackle the tasks of multi-language and arbitrary-oriented text detection, tracking, and script identification in natural scenes.
For this we have developed a set of generic methods that build on top of the basic observation that text has always certain key visual and structural characteristics that are independent of the language or script in which it is written. Text instances in any
language or script are always formed as groups of similar atomic parts, being them either individual characters, small stroke parts, or even whole words in the case of cursive text. This holistic (sumof-parts) and recursive perspective has lead us to explore different variants of the “segmentation and grouping” paradigm of computer vision.
Scene text detection methodologies are usually based in classification of individual regions or patches, using a priory knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organization through which
text emerges as a perceptually significant group of atomic objects.
In this thesis, we argue that the text detection problem must be posed as the detection of meaningful groups of regions. We address the problem of text detection in natural scenes from a hierarchical perspective, making explicit use of the recursive nature of text, 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 hypothese with high recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Within this generic framework, we design a text-specific object proposals algorithm that, contrary to existing generic object proposals methods, aims directly to the detection of text regions groupings. For this, we abandon the rigid definition of “what is text” of traditional specialized text detectors, and move towards more fuzzy perspective of grouping-based object proposals methods.
Then, we present a hybrid algorithm for detection and tracking of scene text where the notion of region groupings plays also a central role. By leveraging the structural arrangement of text group components between consecutive frames we can improve
the overall tracking performance of the system.
Finally, since our generic detection framework is inherently designed for multi-language environments, we focus on the problem of script identification in order to build a multi-language end-toend reading system. Facing this problem with state of the art CNN classifiers is not straightforward, as they fail to address a key
characteristic of scene text instances: their extremely variable aspect ratio. Instead of resizing input images to a fixed size as in the typical use of holistic CNN classifiers, we propose a patch-based classification framework in order to preserve discriminative parts of the image that are characteristic of its class. We describe a novel method based on the use of ensembles of conjoined networks to jointly learn discriminative stroke-parts representations and their relative importance in a patch-based classification scheme.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Place of Publication Editor Dimosthenis Karatzas  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ Gom2016 Serial 2891  
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Author Marçal Rusiñol; Josep Llados edit  doi
openurl 
  Title Flowchart Recognition in Patent Information Retrieval Type Book Chapter
  Year 2017 Publication Current Challenges in Patent Information Retrieval Abbreviated Journal  
  Volume 37 Issue Pages 351-368  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor M. Lupu; K. Mayer; N. Kando; A.J. Trippe  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ RuL2017 Serial 2896  
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Author Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol edit   pdf
openurl 
  Title La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals Type Journal
  Year 2016 Publication Lligall, Revista Catalana d'Arxivística Abbreviated Journal  
  Volume 39 Issue Pages 20-46  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.097 Approved no  
  Call Number Admin @ si @ FLR2016 Serial 2897  
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Author Arnau Baro; Pau Riba; Alicia Fornes edit   pdf
doi  openurl
  Title Towards the recognition of compound music notes in handwritten music scores Type Conference Article
  Year 2016 Publication 15th international conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages  
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  Abstract The recognition of handwritten music scores still remains an open problem. The existing approaches can only deal with very simple handwritten scores mainly because of the variability in the handwriting style and the variability in the composition of groups of music notes (i.e. compound music notes). In this work we focus on this second problem and propose a method based on perceptual grouping for the recognition of compound music notes. Our method has been tested using several handwritten music scores of the CVC-MUSCIMA database and compared with a commercial Optical Music Recognition (OMR) software. Given that our method is learning-free, the obtained results are promising.  
  Address Shenzhen; China; October 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN 2167-6445 ISBN Medium  
  Area Expedition Conference ICFHR  
  Notes DAG; 600.097 Approved no  
  Call Number Admin @ si @ BRF2016 Serial 2903  
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Author Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Anna Cabre edit   pdf
isbn  openurl
  Title Bridging the gap between historical demography and computing: tools for computer-assisted transcription and the analysis of demographic sources Type Book Chapter
  Year 2016 Publication The future of historical demography. Upside down and inside out Abbreviated Journal  
  Volume Issue Pages 127-131  
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  Abstract  
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  Publisher Acco Publishers Place of Publication Editor K.Matthijs; S.Hin; H.Matsuo; J.Kok  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-94-6292-722-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.097 Approved no  
  Call Number Admin @ si @ PFL2016 Serial 2907  
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Author Oriol Vicente; Alicia Fornes; Ramon Valdes edit   pdf
openurl 
  Title The Digital Humanities Network of the UABCie: a smart structure of research and social transference for the digital humanities Type Conference Article
  Year 2016 Publication Digital Humanities Centres: Experiences and Perspectives Abbreviated Journal  
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  Address Warsaw; Poland; December 2016  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title (up)  
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  ISSN ISBN Medium  
  Area Expedition Conference DHLABS  
  Notes DAG; 600.097 Approved no  
  Call Number Admin @ si @ VFV2016 Serial 2908  
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Author Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez edit   pdf
openurl 
  Title Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books Type Conference Article
  Year 2016 Publication 15th international conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Handwritten marriage licenses books have been used for centuries by ecclesiastical and secular institutions to register marriages. The information contained in these historical documents is useful for demography studies and
genealogical research, among others. Despite the generally simple structure of the text in these documents, automatic transcription and semantic information extraction is difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In previous
works we studied the use of category-based language models to both improve the automatic transcription accuracy and make easier the extraction of semantic information. Here we analyze the main causes of the semantic errors observed in previous results and apply a Grammatical Inference technique known as MGGI to improve the semantic accuracy of the language model obtained. Using this language model, full handwritten text recognition experiments have been carried out, with results supporting the interest of the proposed approach.
 
  Address Shenzhen; China; October 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICFHR  
  Notes DAG; 600.097; 602.006 Approved no  
  Call Number Admin @ si @ RFV2016 Serial 2909  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
url  openurl
  Title Product graph-based higher order contextual similarities for inexact subgraph matching Type Journal Article
  Year 2018 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 76 Issue Pages 596-611  
  Keywords  
  Abstract Many algorithms formulate graph matching as an optimization of an objective function of pairwise quantification of nodes and edges of two graphs to be matched. Pairwise measurements usually consider local attributes but disregard contextual information involved in graph structures. We address this issue by proposing contextual similarities between pairs of nodes. This is done by considering the tensor product graph (TPG) of two graphs to be matched, where each node is an ordered pair of nodes of the operand graphs. Contextual similarities between a pair of nodes are computed by accumulating weighted walks (normalized pairwise similarities) terminating at the corresponding paired node in TPG. Once the contextual similarities are obtained, we formulate subgraph matching as a node and edge selection problem in TPG. We use contextual similarities to construct an objective function and optimize it with a linear programming approach. Since random walk formulation through TPG takes into account higher order information, it is not a surprise that we obtain more reliable similarities and better discrimination among the nodes and edges. Experimental results shown on synthetic as well as real benchmarks illustrate that higher order contextual similarities increase discriminating power and allow one to find approximate solutions to the subgraph matching problem.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title (up)  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 602.167; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ DLB2018 Serial 3083  
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