|
Records |
Links |
|
Author |
Arnau Baro; Pau Riba; Alicia Fornes |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Towards the recognition of compound music notes in handwritten music scores |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
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 |
|
|
|
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 |
|
Permanent link to this record |
|
|
|
|
Author |
Oriol Vicente; Alicia Fornes; Ramon Valdes |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
|
|
Title |
The Digital Humanities Network of the UABCie: a smart structure of research and social transference for the digital humanities |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2016 |
Publication |
Digital Humanities Centres: Experiences and Perspectives |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Warsaw; Poland; December 2016 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
DHLABS |
|
|
Notes |
DAG; 600.097 |
Approved |
no |
|
|
Call Number |
Admin @ si @ VFV2016 |
Serial |
2908 |
|
Permanent link to this record |
|
|
|
|
Author |
Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
|
|
Title |
Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
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 |
|
|
|
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 |
Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Graph Embedding through Probabilistic Graphical Model applied to Symbolic Graphs |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
8th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
Attributed Graph; Probabilistic Graphical Model; Graph Embedding; Structured Support Vector Machines |
|
|
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. |
|
|
Address |
Faro; Portugal; June 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ JRL2017a |
Serial |
2953 |
|
Permanent link to this record |
|
|
|
|
Author |
Lasse Martensson; Anders Hast; Alicia Fornes |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Word Spotting as a Tool for Scribal Attribution |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
2nd Conference of the association of Digital Humanities in the Nordic Countries |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
87-89 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Gothenburg; Suecia; March 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-91-88348-83-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
DHN |
|
|
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MHF2017 |
Serial |
2954 |
|
Permanent link to this record |
|
|
|
|
Author |
Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
Learning structural loss parameters on graph embedding applied on symbolic graphs |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
12th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
We propose an amelioration of proposed Graph Embedding (GEM) method in previous work that takes advantages of structural pattern representation and the structured distortion. it models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector, as new signature of AG in a lower dimensional vectorial space. We focus to adapt the structured learning algorithm via 1_slack formulation with a suitable risk function, called Graph Edit Distance (GED). It defines the dissimilarity of the ground truth and predicted graph labels. It determines by the error tolerant graph matching using bipartite graph matching algorithm. We apply Structured Support Vector Machines (SSVM) to process classification task. During our experiments, we got our results on the GREC dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GREC |
|
|
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ JRL2017b |
Serial |
3073 |
|
Permanent link to this record |
|
|
|
|
Author |
J. Chazalon; P. Gomez-Kramer; Jean-Christophe Burie; M.Coustaty; S.Eskenazi; Muhammad Muzzamil Luqman; Nibal Nayef; Marçal Rusiñol; N. Sidere; Jean-Marc Ogier |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
SmartDoc 2017 Video Capture: Mobile Document Acquisition in Video Mode |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
1st International Workshop on Open Services and Tools for Document Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
As mobile document acquisition using smartphones is getting more and more common, along with the continuous improvement of mobile devices (both in terms of computing power and image quality), we can wonder to which extent mobile phones can replace desktop scanners. Modern applications can cope with perspective distortion and normalize the contrast of a document page captured with a smartphone, and in some cases like bottle labels or posters, smartphones even have the advantage of allowing the acquisition of non-flat or large documents. However, several cases remain hard to handle, such as reflective documents (identity cards, badges, glossy magazine cover, etc.) or large documents for which some regions require an important amount of detail. This paper introduces the SmartDoc 2017 benchmark (named “SmartDoc Video Capture”), which aims at
assessing whether capturing documents using the video mode of a smartphone could solve those issues. The task under evaluation is both a stitching and a reconstruction problem, as the user can move the device over different parts of the document to capture details or try to erase highlights. The material released consists of a dataset, an evaluation method and the associated tool, a sample method, and the tools required to extend the dataset. All the components are released publicly under very permissive licenses, and we particularly cared about maximizing the ease of
understanding, usage and improvement. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR-OST |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ CGB2017 |
Serial |
2997 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
LSDE: Levenshtein Space Deep Embedding for Query-by-string Word Spotting |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
n this paper we present the LSDE string representation and its application to handwritten word spotting. LSDE is a novel embedding approach for representing strings that learns a space in which distances between projected points are correlated with the Levenshtein edit distance between the original strings.
We show how such a representation produces a more semantically interpretable retrieval from the user’s perspective than other state of the art ones such as PHOC and DCToW. We also conduct a preliminary handwritten word spotting experiment on the George Washington dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GRK2017 |
Serial |
2999 |
|
Permanent link to this record |
|
|
|
|
Author |
E. Royer; J. Chazalon; Marçal Rusiñol; F. Bouchara |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Benchmarking Keypoint Filtering Approaches for Document Image Matching |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Best Poster Award.
Reducing the amount of keypoints used to index an image is particularly interesting to control processing time and memory usage in real-time document image matching applications, like augmented documents or smartphone applications. This paper benchmarks two keypoint selection methods on a task consisting of reducing keypoint sets extracted from document images, while preserving detection and segmentation accuracy. We first study the different forms of keypoint filtering, and we introduce the use of the CORE selection method on
keypoints extracted from document images. Then, we extend a previously published benchmark by including evaluations of the new method, by adding the SURF-BRISK detection/description scheme, and by reporting processing speeds. Evaluations are conducted on the publicly available dataset of ICDAR2015 SmartDOC challenge 1. Finally, we prove that reducing the original keypoint set is always feasible and can be beneficial
not only to processing speed but also to accuracy. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RCR2017 |
Serial |
3000 |
|
Permanent link to this record |
|
|
|
|
Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Automatic Static/Variable Content Separation in Administrative Document Images |
Type ![sorted by Type field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
In this paper we present an automatic method for separating static and variable content from administrative document images. An alignment approach is able to unsupervisedly build probabilistic templates from a set of examples of the same document kind. Such templates define which is the likelihood of every pixel of being either static or variable content. In the extraction step, the same alignment technique is used to match
an incoming image with the template and to locate the positions where variable fields appear. We validate our approach on the public NIST Structured Tax Forms Dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ART2017 |
Serial |
3001 |
|
Permanent link to this record |