| Records |
| Author |
Marçal Rusiñol; Agnes Borras; Josep Llados |
| Title |
Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images |
Type |
Journal Article |
| Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume  |
31 |
Issue |
3 |
Pages |
188–201 |
| Keywords |
Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings |
| Abstract |
This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results. |
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Elsevier |
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DAG |
Approved |
no |
| Call Number |
DAG @ dag @ RBL2010 |
Serial |
1177 |
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| Author |
Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
| Title |
Unsupervised writer adaptation of whole-word HMMs with application to word-spotting |
Type |
Journal Article |
| Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
31 |
Issue |
8 |
Pages |
742–749 |
| Keywords |
Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis |
| Abstract |
In this paper we propose a novel approach for writer adaptation in a handwritten word-spotting task. The method exploits the fact that the semi-continuous hidden Markov model separates the word model parameters into (i) a codebook of shapes and (ii) a set of word-specific parameters.
Our main contribution is to employ this property to derive writer-specific word models by statistically adapting an initial universal codebook to each document. This process is unsupervised and does not even require the appearance of the keyword(s) in the searched document. Experimental results show an increase in performance when this adaptation technique is applied. To the best of our knowledge, this is the first work dealing with adaptation for word-spotting. The preliminary version of this paper obtained an IBM Best Student Paper Award at the 19th International Conference on Pattern Recognition. |
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Elsevier |
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DAG |
Approved |
no |
| Call Number |
DAG @ dag @ RPS2010 |
Serial |
1290 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Re-coding ECOCs without retraining |
Type |
Journal Article |
| Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
31 |
Issue |
7 |
Pages |
555–562 |
| Keywords |
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| Abstract |
A standard way to deal with multi-class categorization problems is by the combination of binary classifiers in a pairwise voting procedure. Recently, this classical approach has been formalized in the Error-Correcting Output Codes (ECOC) framework. In the ECOC framework, the one-versus-one coding demonstrates to achieve higher performance than the rest of coding designs. The binary problems that we train in the one-versus-one strategy are significantly smaller than in the rest of designs, and usually easier to be learnt, taking into account the smaller overlapping between classes. However, a high percentage of the positions coded by zero of the coding matrix, which implies a high sparseness degree, does not codify meta-class membership information. In this paper, we show that using the training data we can redefine without re-training, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information helps the system to increase its generalization capability. Moreover, the new re-coding strategy is generalized to be applied over any binary code. The results over several UCI Machine Learning repository data sets and two real multi-class problems show that performance improvements can be obtained re-coding the classical one-versus-one and Sparse random designs compared to different state-of-the-art ECOC configurations. |
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Elsevier |
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| Notes |
MILAB;HUPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2010e |
Serial |
1338 |
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| Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa |
| Title |
Median graph: A new exact algorithm using a distance based on the maximum common subgraph |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
30 |
Issue |
5 |
Pages |
579–588 |
| Keywords |
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| Abstract |
Median graphs have been presented as a useful tool for capturing the essential information of a set of graphs. Nevertheless, computation of optimal solutions is a very hard problem. In this work we present a new and more efficient optimal algorithm for the median graph computation. With the use of a particular cost function that permits the definition of the graph edit distance in terms of the maximum common subgraph, and a prediction function in the backtracking algorithm, we reduce the size of the search space, avoiding the evaluation of a great amount of states and still obtaining the exact median. We present a set of experiments comparing our new algorithm against the previous existing exact algorithm using synthetic data. In addition, we present the first application of the exact median graph computation to real data and we compare the results against an approximate algorithm based on genetic search. These experimental results show that our algorithm outperforms the previous existing exact algorithm and in addition show the potential applicability of the exact solutions to real problems. |
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Elsevier Science Inc. |
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| ISSN |
0167-8655 |
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| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ FVS2009a |
Serial |
1114 |
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| Author |
Fadi Dornaika; Angel Sappa |
| Title |
Instantaneous 3D motion from image derivatives using the Least Trimmed Square Regression |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
30 |
Issue |
5 |
Pages |
535–543 |
| Keywords |
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| Abstract |
This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes. |
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Elsevier Science Inc. |
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Edition |
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0167-8655 |
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Conference |
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| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ DoS2009a |
Serial |
1115 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Separability of Ternary Codes for Sparse Designs of Error-Correcting Output Codes |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
30 |
Issue |
3 |
Pages |
285–297 |
| Keywords |
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| Abstract |
Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new Sparse Random coding matrix with ternary distance maximization. The results on the UCI Repository and in a real speed traffic categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied. |
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| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2009a |
Serial |
1153 |
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| Author |
Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados |
| Title |
Blurred Shape Model for Binary and Grey-level Symbol Recognition |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
30 |
Issue |
15 |
Pages |
1424–1433 |
| Keywords |
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| Abstract |
Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance. |
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| Notes |
HuPBA; DAG; MILAB |
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no |
| Call Number |
BCNPCL @ bcnpcl @ EFP2009a |
Serial |
1180 |
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| Author |
Fadi Dornaika; Angel Sappa |
| Title |
Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models |
Type |
Journal Article |
| Year |
2007 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
28 |
Issue |
15 |
Pages |
2116-2126 |
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ADAS |
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no |
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ADAS @ adas @ DoS2007c |
Serial |
877 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
A new use of the ridgelets transform for describing linear singularities in images |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
6 |
Pages |
587–596 |
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DAG |
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no |
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DAG @ dag @ RaV2006a |
Serial |
635 |
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| Author |
Jaume Amores; N. Sebe; Petia Radeva |
| Title |
Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
3 |
Pages |
201–209 |
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ADAS;MILAB |
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no |
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ADAS @ adas @ ASR2006 |
Serial |
643 |
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| Author |
Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva |
| Title |
ROC curves and video analysis optimization in intestinal capsule endoscopy |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
8 |
Pages |
875–881 |
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ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy |
| Abstract |
Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions. |
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800 |
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MILAB;MV;SIAI |
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no |
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BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 |
Serial |
647 |
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| Author |
Xavier Otazu; Oriol Pujol |
| Title |
Wavelet based approach to cluster analysis. Application on low dimensional data sets |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
14 |
Pages |
1590–1605 |
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MILAB; CIC; HuPBA |
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no |
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BCNPCL @ bcnpcl @ OtP2006 |
Serial |
658 |
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| Author |
Debora Gil; Petia Radeva |
| Title |
Inhibition of false landmarks |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
9 |
Pages |
1022-1030 |
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| Abstract |
Corners and junctions are landmarks characterized by the lack of differentiability in the unit tangent to the image level curve. Detectors based on differential operators are not, by their own definition, the best posed as they require a higher degree of differentiability to yield a reliable response. We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our inhibition orientation energy (IOE) landmark locator. |
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Elsevier Science Inc. |
Place of Publication |
New York, NY, USA |
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0167-8655 |
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| Notes |
IAM;MILAB |
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no |
| Call Number |
IAM @ iam @ GiR2006 |
Serial |
1529 |
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| Author |
A. Sanfeliu; Juan J. Villanueva |
| Title |
An approach of visual motion analysis |
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Journal Article |
| Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
26 |
Issue |
3 |
Pages |
355–368 |
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IF: 1.138 |
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ISE @ ise @ SaV2005 |
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561 |
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| Author |
Jaume Amores; Petia Radeva |
| Title |
Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
Type |
Journal Article |
| Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
26 |
Issue |
11 |
Pages |
1720–1731 |
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| Abstract |
IF: 1.138 |
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ADAS;MILAB |
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no |
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ADAS @ adas @ AmR2005b |
Serial |
592 |
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