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Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone |
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Title |
Towards Modelling an Attention-Based Text Localization Process |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
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Pages |
296-303 |
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Keywords |
text localization; visual attention; eye guidance |
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Abstract |
This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms.
Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented. |
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Address |
Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38627-5 |
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IbPRIA |
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DAG |
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no |
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Call Number |
Admin @ si @ CKL2013 |
Serial |
2291 |
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Author |
Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados |
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Title |
Hybrid grammar language model for handwritten historical documents recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
Issue |
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Pages |
117-124 |
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Abstract |
In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate. |
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Address |
Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38627-5 |
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IbPRIA |
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Notes |
DAG; 602.006; 600.045; 600.061 |
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no |
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Call Number |
Admin @ si @ CFF2013 |
Serial |
2292 |
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Author |
Suman Ghosh; Ernest Valveny |
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Title |
A Sliding Window Framework for Word Spotting Based on Word Attributes |
Type |
Conference Article |
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Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
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Volume |
9117 |
Issue |
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Pages |
652-661 |
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Keywords |
Word spotting; Sliding window; Word attributes |
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Abstract |
In this paper we propose a segmentation-free approach to word spotting. Word images are first encoded into feature vectors using Fisher Vector. Then, these feature vectors are used together with pyramidal histogram of characters labels (PHOC) to learn SVM-based attribute models. Documents are represented by these PHOC based word attributes. To efficiently compute the word attributes over a sliding window, we propose to use an integral image representation of the document using a simplified version of the attribute model. Finally we re-rank the top word candidates using the more discriminative full version of the word attributes. We show state-of-the-art results for segmentation-free query-by-example word spotting in single-writer and multi-writer standard datasets. |
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Address |
Santiago de Compostela; June 2015 |
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Springer International Publishing |
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0302-9743 |
ISBN |
978-3-319-19389-2 |
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IbPRIA |
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Notes |
DAG; 600.077 |
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no |
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Call Number |
Admin @ si @ GhV2015b |
Serial |
2716 |
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Author |
Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
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Title |
Information Extraction in Handwritten Marriage Licenses Books Using the MGGI Methodology |
Type |
Conference Article |
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Year |
2017 |
Publication |
8th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
10255 |
Issue |
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Pages |
287-294 |
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Keywords |
Handwritten Text Recognition; Information extraction; Language modeling; MGGI; Categories-based language model |
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Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demographic and genealogical research. For example, marriage license books have been used for centuries by ecclesiastical and secular institutions to register marriages. These books follow a simple structure of the text in the records with a evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. In previous works we studied the use of category-based language models and how a Grammatical Inference technique known as MGGI could improve the accuracy of these tasks. In this work we analyze the main causes of the semantic errors observed in previous results and apply a better implementation of the MGGI technique to solve these problems. Using the resulting language model, transcription and information extraction experiments have been carried out, and the results support our proposed approach. |
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Address |
Faro; Portugal; June 2017 |
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L.A. Alexandre; J.Salvador Sanchez; Joao M. F. Rodriguez |
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ISBN |
978-3-319-58837-7 |
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IbPRIA |
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Notes |
DAG; 602.006; 600.097; 600.121 |
Approved |
no |
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Call Number |
Admin @ si @ RFV2017 |
Serial |
2952 |
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Author |
Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
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Title |
Graph Embedding through Probabilistic Graphical Model applied to Symbolic Graphs |
Type |
Conference Article |
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Year |
2017 |
Publication |
8th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Keywords |
Attributed Graph; Probabilistic Graphical Model; Graph Embedding; Structured Support Vector Machines |
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Abstract |
We propose a new Graph Embedding (GEM) method that takes advantages of structural pattern representation. It models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector. This vector is a signature of AG in a lower dimensional vectorial space. We apply Structured Support Vector Machines (SSVM) to process classification task. As first tentative, results on the GREC dataset are encouraging enough to go further on this direction. |
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Faro; Portugal; June 2017 |
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IbPRIA |
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Notes |
DAG; 600.097; 600.121 |
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no |
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Call Number |
Admin @ si @ JRL2017a |
Serial |
2953 |
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Author |
Oriol Ramos Terrades; Salvatore Tabbone; Ernest Valveny |
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Title |
Optimal Linear Combination for Two-class Classifiers |
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Conference Article |
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Year |
2007 |
Publication |
Proceedings of the International Conference on Advances in Pattern Recognition |
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Kolkata (India) |
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ICAPR |
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DAG |
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Call Number |
DAG @ dag @ RTV2007a |
Serial |
894 |
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Author |
Partha Pratim Roy; Josep Llados |
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Title |
Multi-Oriented Character Recognition from Graphical Documents |
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Conference Article |
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Year |
2008 |
Publication |
2nd International Conference on Cognition and Recognition |
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Pages |
30–35 |
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Address |
Mandya (India) |
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ICCR |
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DAG |
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no |
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Call Number |
DAG @ dag @ RLP2008 |
Serial |
965 |
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Author |
Partha Pratim Roy; Josep Llados; Umapada Pal |
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Title |
Text/Graphics Separation in Color Maps |
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Conference Article |
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Year |
2007 |
Publication |
International Conference on Computing: Theory and Applications |
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545–551 |
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Kolkata (India) |
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ICCTA |
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DAG |
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Call Number |
DAG @ dag @ RLP2007a |
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806 |
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Author |
Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny |
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Title |
Handwritten Word Spotting with Corrected Attributes |
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Conference Article |
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Year |
2013 |
Publication |
15th IEEE International Conference on Computer Vision |
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Pages |
1017-1024 |
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Abstract |
We propose an approach to multi-writer word spotting, where the goal is to find a query word in a dataset comprised of document images. We propose an attributes-based approach that leads to a low-dimensional, fixed-length representation of the word images that is fast to compute and, especially, fast to compare. This approach naturally leads to an unified representation of word images and strings, which seamlessly allows one to indistinctly perform query-by-example, where the query is an image, and query-by-string, where the query is a string. We also propose a calibration scheme to correct the attributes scores based on Canonical Correlation Analysis that greatly improves the results on a challenging dataset. We test our approach on two public datasets showing state-of-the-art results. |
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Sydney; Australia; December 2013 |
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ISSN |
1550-5499 |
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Conference |
ICCV |
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Notes |
DAG |
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no |
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Call Number |
Admin @ si @ AGF2013 |
Serial |
2327 |
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Author |
Ali Furkan Biten; Ruben Tito; Andres Mafla; Lluis Gomez; Marçal Rusiñol; C.V. Jawahar; Ernest Valveny; Dimosthenis Karatzas |
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Title |
Scene Text Visual Question Answering |
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Conference Article |
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Year |
2019 |
Publication |
18th IEEE International Conference on Computer Vision |
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Pages |
4291-4301 |
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Abstract |
Current visual question answering datasets do not consider the rich semantic information conveyed by text within an image. In this work, we present a new dataset, ST-VQA, that aims to highlight the importance of exploiting highlevel semantic information present in images as textual cues in the Visual Question Answering process. We use this dataset to define a series of tasks of increasing difficulty for which reading the scene text in the context provided by the visual information is necessary to reason and generate an appropriate answer. We propose a new evaluation metric for these tasks to account both for reasoning errors as well as shortcomings of the text recognition module. In addition we put forward a series of baseline methods, which provide further insight to the newly released dataset, and set the scene for further research. |
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Address |
Seul; Corea; October 2019 |
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ICCV |
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Notes |
DAG; 600.129; 600.135; 601.338; 600.121 |
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Call Number |
Admin @ si @ BTM2019b |
Serial |
3285 |
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