toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author D. Perez; L. Tarazon; N. Serrano; F.M. Castro; Oriol Ramos Terrades; A. Juan edit  doi
isbn  openurl
  Title The GERMANA Database Type Conference Article
  Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 301-305  
  Keywords (down)  
  Abstract A new handwritten text database, GERMANA, is presented to facilitate empirical comparison of different approaches to text line extraction and off-line handwriting recognition. GERMANA is the result of digitising and annotating a 764-page Spanish manuscript from 1891, in which most pages only contain nearly calligraphed text written on ruled sheets of well-separated lines. To our knowledge, it is the first publicly available database for handwriting research, mostly written in Spanish and comparable in size to standard databases. Due to its sequential book structure, it is also well-suited for realistic assessment of interactive handwriting recognition systems. To provide baseline results for reference in future studies, empirical results are also reported, using standard techniques and tools for preprocessing, feature extraction, HMM-based image modelling, and language modelling.  
  Address Barcelona; Spain  
  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 1520-5363 ISBN 978-1-4244-4500-4 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ PTS2009 Serial 1870  
Permanent link to this record
 

 
Author L.Tarazon; D. Perez; N. Serrano; V. Alabau; Oriol Ramos Terrades; A. Sanchis; A. Juan edit  doi
isbn  openurl
  Title Confidence Measures for Error Correction in Interactive Transcription of Handwritten Text Type Conference Article
  Year 2009 Publication 15th International Conference on Image Analysis and Processing Abbreviated Journal  
  Volume 5716 Issue Pages 567-574  
  Keywords (down)  
  Abstract An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence.  
  Address Vietri sul Mare, Italy  
  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 978-3-642-04145-7 Medium  
  Area Expedition Conference ICIAP  
  Notes DAG Approved no  
  Call Number Admin @ si @ TPS2009 Serial 1871  
Permanent link to this record
 

 
Author H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent edit  doi
openurl 
  Title Feature Selection Combining Genetic Algorithm and Adaboost Classifiers Type Conference Article
  Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1-4  
  Keywords (down)  
  Abstract  
  Address Tampa, Florida  
  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 ICPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ CRT2008 Serial 1872  
Permanent link to this record
 

 
Author T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades edit  openurl
  Title Symbol Descriptor Based on Shape Context and Vector Model of Information Retrieval Type Conference Article
  Year 2008 Publication Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, Abbreviated Journal  
  Volume Issue Pages 191-197  
  Keywords (down)  
  Abstract  
  Address Nara, Japan  
  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 DAS  
  Notes DAG Approved no  
  Call Number Admin @ si @ NTR2008a Serial 1873  
Permanent link to this record
 

 
Author H. Chouaib; Salvatore Tabbone; Oriol Ramos Terrades; F. Cloppet; N. Vincent; A.T. Thierry Paquet edit  openurl
  Title Sélection de Caractéristiques à partir d'un algorithme génétique et d'une combinaison de classifieurs Adaboost Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l'Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 181-186  
  Keywords (down)  
  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 @ CTR2008 Serial 1874  
Permanent link to this record
 

 
Author T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades; A.T. Thierry edit  openurl
  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 79-84  
  Keywords (down)  
  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 Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat edit  doi
openurl 
  Title Histogram of radon transform. A useful descriptor for shape retrieval Type Conference Article
  Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1-4  
  Keywords (down)  
  Abstract  
  Address Tampa, Florida  
  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 ICPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ TRB2008 Serial 1876  
Permanent link to this record
 

 
Author M. Visani; V.C.Kieu; Alicia Fornes; N.Journet edit   pdf
doi  openurl
  Title The ICDAR 2013 Music Scores Competition: Staff Removal Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1439-1443  
  Keywords (down)  
  Abstract The first competition on music scores that was organized at ICDAR in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario: old music scores. For this purpose, we have generated a new set of images using two kinds of degradations: local noise and 3D distortions. This paper describes the dataset, distortion methods, evaluation metrics, the participant's methods and the obtained results.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.045; 600.061 Approved no  
  Call Number Admin @ si @ VKF2013 Serial 2338  
Permanent link to this record
 

 
Author Sergio Escalera; Ana Puig; Oscar Amoros; Maria Salamo edit  doi
openurl 
  Title Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes Type Journal Article
  Year 2011 Publication Computer Graphics Forum Abbreviated Journal CGF  
  Volume 30 Issue 7 Pages 2107-2115  
  Keywords (down)  
  Abstract IF JCR 1.455 2010 25/99
In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent methods to label on-demand multiple regions of interest. These methods can be split into a two-level GPU-based labelling algorithm that computes in time of rendering a set of labelled structures using the Machine Learning Error-Correcting Output Codes (ECOC) framework. In a pre-processing step, ECOC trains a set of Adaboost binary classifiers from a reduced pre-labelled data set. Then, at the testing stage, each classifier is independently applied on the features of a set of unlabelled samples and combined to perform multi-class labelling. We also propose an alternative representation of these classifiers that allows to highly parallelize the testing stage. To exploit that parallelism we implemented the testing stage in GPU-OpenCL. The empirical results on different data sets for several volume structures shows high computational performance and classification accuracy.
 
  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 ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ EPA2011 Serial 1881  
Permanent link to this record
 

 
Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria edit  url
doi  openurl
  Title Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models Type Journal Article
  Year 2011 Publication PloS one Abbreviated Journal Plos  
  Volume 6 Issue 8 Pages e23323  
  Keywords (down)  
  Abstract JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
 
  Address  
  Corporate Author Thesis  
  Publisher Public Library of Science 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  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RMT2011 Serial 1883  
Permanent link to this record
 

 
Author Bogdan Raducanu; Fadi Dornaika edit   pdf
url  doi
openurl 
  Title A Supervised Non-linear Dimensionality Reduction Approach for Manifold Learning Type Journal Article
  Year 2012 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 45 Issue 6 Pages 2432-2444  
  Keywords (down)  
  Abstract IF= 2.61
IF=2.61 (2010)
In this paper we introduce a novel supervised manifold learning technique called Supervised Laplacian Eigenmaps (S-LE), which makes use of class label information to guide the procedure of non-linear dimensionality reduction by adopting the large margin concept. The graph Laplacian is split into two components: within-class graph and between-class graph to better characterize the discriminant property of the data. Our approach has two important characteristics: (i) it adaptively estimates the local neighborhood surrounding each sample based on data density and similarity and (ii) the objective function simultaneously maximizes the local margin between heterogeneous samples and pushes the homogeneous samples closer to each other.

Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques, demonstrating its superiority. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variations in their appearance (such as hand or body pose, for instance.
 
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0031-3203 ISBN Medium  
  Area Expedition Conference  
  Notes OR; MV Approved no  
  Call Number Admin @ si @ RaD2012a Serial 1884  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu edit   pdf
doi  openurl
  Title Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction Type Journal Article
  Year 2012 Publication Sensors Abbreviated Journal SENS  
  Volume 12 Issue 2 Pages 1702-1719  
  Keywords (down)  
  Abstract IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
 
  Address  
  Corporate Author Thesis  
  Publisher Molecular Diversity Preservation International 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  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ EBV2012 Serial 1885  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  url
doi  isbn
openurl 
  Title On the Design of Low Redundancy Error-Correcting Output Codes Type Book Chapter
  Year 2011 Publication Ensembles in Machine Learning Applications Abbreviated Journal  
  Volume 373 Issue 2 Pages 21-38  
  Keywords (down)  
  Abstract The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1860-949X ISBN 978-3-642-22909-1 Medium  
  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BEB2011b Serial 1886  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera edit  url
isbn  openurl
  Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
  Year 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 227-236  
  Keywords (down)  
  Abstract Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.  
  Address Napoles, Italy  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium  
  Area Expedition Conference MCS  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BPB2011b Serial 1887  
Permanent link to this record
 

 
Author Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu edit   pdf
openurl 
  Title LSDA Solution Schemes for Modelless 3D Head Pose Estimation Type Conference Article
  Year 2012 Publication IEEE Workshop on the Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 393-398  
  Keywords (down)  
  Abstract  
  Address Breckenridge; USA;  
  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 WACV  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ DBR2012 Serial 1889  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: