|
Records |
Links |
|
Author |
Marçal Rusiñol; Josep Llados |
![goto web page url](http://refbase.cvc.uab.es/img/www.gif)
|
|
Title |
A Performance Evaluation Protocol for Symbol Spotting Systems in Terms of Recognition and Location Indices |
Type |
Journal Article |
|
Year |
2009 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
|
|
Volume |
12 |
Issue |
2 |
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
83-96 |
|
|
Keywords |
Performance evaluation; Symbol Spotting; Graphics Recognition |
|
|
Abstract |
Symbol spotting systems are intended to retrieve regions of interest from a document image database where the queried symbol is likely to be found. They shall have the ability to recognize and locate graphical symbols in a single step. In this paper, we present a set of measures to evaluate the performance of a symbol spotting system in terms of recognition abilities, location accuracy and scalability. We show that the proposed measures allow to determine the weaknesses and strengths of different methods. In particular we have tested a symbol spotting method based on a set of four different off-the-shelf shape descriptors. |
|
|
Address |
|
|
|
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 |
1433-2833 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
DAG @ dag @ RuL2009a |
Serial |
1166 |
|
Permanent link to this record |
|
|
|
|
Author |
Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors |
Type |
Conference Article |
|
Year |
2011 |
Publication |
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
83-90 |
|
|
Keywords |
|
|
|
Abstract |
The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
ACM |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-4503-0916-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
HIP |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ FFF2011a |
Serial |
1823 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Torras; Mohamed Ali Souibgui; Sanket Biswas; Alicia Fornes |
![goto web page url](http://refbase.cvc.uab.es/img/www.gif)
|
|
Title |
Segmentation-Free Alignment of Arbitrary Symbol Transcripts to Images |
Type |
Conference Article |
|
Year |
2023 |
Publication |
Document Analysis and Recognition – ICDAR 2023 Workshops |
Abbreviated Journal |
|
|
|
Volume |
14193 |
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
83-93 |
|
|
Keywords |
Historical Manuscripts; Symbol Alignment |
|
|
Abstract |
Developing arbitrary symbol recognition systems is a challenging endeavour. Even using content-agnostic architectures such as few-shot models, performance can be substantially improved by providing a number of well-annotated examples into training. In some contexts, transcripts of the symbols are available without any position information associated to them, which enables using line-level recognition architectures. A way of providing this position information to detection-based architectures is finding systems that can align the input symbols with the transcription. In this paper we discuss some symbol alignment techniques that are suitable for low-data scenarios and provide an insight on their perceived strengths and weaknesses. In particular, we study the usage of Connectionist Temporal Classification models, Attention-Based Sequence to Sequence models and we compare them with the results obtained on a few-shot recognition system. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ TSS2023 |
Serial |
3850 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Salvatore Tabbone; Oriol Ramos Terrades; Emilie Jean-Marie Odile |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Performance Characterization of Shape Descriptors for Symbol Representation |
Type |
Conference Article |
|
Year |
2007 |
Publication |
Seventh IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
82–83 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Curitiba (Brazil) |
|
|
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 |
Approved |
no |
|
|
Call Number |
DAG @ dag @ VTR2007 |
Serial |
889 |
|
Permanent link to this record |
|
|
|
|
Author |
N. Serrano; L. Tarazon; D. Perez; Oriol Ramos Terrades; S. Juan |
![find book details (via ISBN) isbn](http://refbase.cvc.uab.es/img/isbn.gif)
|
|
Title |
The GIDOC Prototype |
Type |
Conference Article |
|
Year |
2010 |
Publication |
10th International Workshop on Pattern Recognition in Information Systems |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
82-89 |
|
|
Keywords |
|
|
|
Abstract |
Transcription of handwritten text in (old) documents is an important, time-consuming task for digital libraries. It might be carried out by first processing all document images off-line, and then manually supervising system transcriptions to edit incorrect parts. However, current techniques for automatic page layout analysis, text line detection and handwriting recognition are still far from perfect, and thus post-editing system output is not clearly better than simply ignoring it.
A more effective approach to transcribe old text documents is to follow an interactive- predictive paradigm in which both, the system is guided by the user, and the user is assisted by the system to complete the transcription task as efficiently as possible. Following this approach, a system prototype called GIDOC (Gimp-based Interactive transcription of old text DOCuments) has been developed to provide user-friendly, integrated support for interactive-predictive layout analysis, line detection and handwriting transcription.
GIDOC is designed to work with (large) collections of homogeneous documents, that is, of similar structure and writing styles. They are annotated sequentially, by (par- tially) supervising hypotheses drawn from statistical models that are constantly updated with an increasing number of available annotated documents. And this is done at different annotation levels. For instance, at the level of page layout analysis, GIDOC uses a novel text block detection method in which conventional, memoryless techniques are improved with a “history” model of text block positions. Similarly, at the level of text line image transcription, GIDOC includes a handwriting recognizer which is steadily improved with a growing number of (partially) supervised transcriptions. |
|
|
Address |
Funchal, Portugal |
|
|
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 |
978-989-8425-14-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
PRIS |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ STP2010 |
Serial |
1868 |
|
Permanent link to this record |
|
|
|
|
Author |
Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find book details (via ISBN) isbn](http://refbase.cvc.uab.es/img/isbn.gif)
|
|
Title |
Optical Music Recognition by Long Short-Term Memory Networks |
Type |
Book Chapter |
|
Year |
2018 |
Publication |
Graphics Recognition. Current Trends and Evolutions |
Abbreviated Journal |
|
|
|
Volume |
11009 |
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
81-95 |
|
|
Keywords |
Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory |
|
|
Abstract |
Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
A. Fornes, B. Lamiroy |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-030-02283-9 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GREC |
|
|
Notes |
DAG; 600.097; 601.302; 601.330; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BRC2018 |
Serial |
3227 |
|
Permanent link to this record |
|
|
|
|
Author |
Asma Bensalah; Pau Riba; Alicia Fornes; Josep Llados |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
|
|
Title |
Shoot less and Sketch more: An Efficient Sketch Classification via Joining Graph Neural Networks and Few-shot Learning |
Type |
Conference Article |
|
Year |
2019 |
Publication |
13th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
80-85 |
|
|
Keywords |
Sketch classification; Convolutional Neural Network; Graph Neural Network; Few-shot learning |
|
|
Abstract |
With the emergence of the touchpad devices and drawing tablets, a new era of sketching started afresh. However, the recognition of sketches is still a tough task due to the variability of the drawing styles. Moreover, in some application scenarios there is few labelled data available for training,
which imposes a limitation for deep learning architectures. In addition, in many cases there is a need to generate models able to adapt to new classes. In order to cope with these limitations, we propose a method based on few-shot learning and graph neural networks for classifying sketches aiming for an efficient neural model. We test our approach with several databases of
sketches, showing promising results. |
|
|
Address |
Sydney; Australia; September 2019 |
|
|
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; 600.140; 601.302; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BRF2019 |
Serial |
3354 |
|
Permanent link to this record |
|
|
|
|
Author |
Partha Pratim Roy; Eduard Vazquez; Josep Llados; Ramon Baldrich; Umapada Pal |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
A System to Retrieve Text/Symbols from Color Maps using Connected Component and Skeleton Analysis |
Type |
Conference Article |
|
Year |
2007 |
Publication |
Seventh IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
79–78 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Curitiba (Brasil) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
J. Llados, W. Liu, J.M. Ogier |
|
|
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 |
CAT; DAG;CIC |
Approved |
no |
|
|
Call Number |
CAT @ cat @ RVL2007 |
Serial |
836 |
|
Permanent link to this record |
|
|
|
|
Author |
T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades; A.T. Thierry |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Proposition d'un descripteur de formes et du modèle vectoriel pour la recherche de symboles |
Type |
Conference Article |
|
Year |
2008 |
Publication |
Colloque International Francophone sur l'Ecrit et le Document |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
79-84 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Rouen, France |
|
|
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 |
CIFED |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ NTR2008b |
Serial |
1875 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find book details (via ISBN) isbn](http://refbase.cvc.uab.es/img/isbn.gif)
|
|
Title |
Notation-invariant patch-based wall detector in architectural floor plans |
Type |
Book Chapter |
|
Year |
2013 |
Publication |
Graphics Recognition. New Trends and Challenges |
Abbreviated Journal |
|
|
|
Volume |
7423 |
Issue |
|
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
79--88 |
|
|
Keywords |
|
|
|
Abstract |
Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-36823-3 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.045; 600.056; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ HMS2013 |
Serial |
2322 |
|
Permanent link to this record |