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Author |
M. Bressan; Jordi Vitria |
Title |
Nonparametric Discriminant Analysis and Nearest Neighbor Classification |
Type |
Journal Article |
Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
24 |
Issue |
15 |
Pages |
2743–2749 |
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IF: 0.809 |
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OR;MV |
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BCNPCL @ bcnpcl @ BrV2003b |
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367 |
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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 |
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877 |
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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 |
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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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HuPBA; DAG; MILAB |
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BCNPCL @ bcnpcl @ EFP2009a |
Serial |
1180 |
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Author |
Ernest Valveny; Enric Marti |
Title |
A model for image generation and symbol recognition through the deformation of lineal shapes |
Type |
Journal Article |
Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
24 |
Issue |
15 |
Pages |
2857-2867 |
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Abstract |
We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. |
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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 |
DAG; IAM |
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no |
Call Number |
IAM @ iam @ VAM2003 |
Serial |
1653 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
Title |
Feature Selection on Node Statistics Based Embedding of Graphs |
Type |
Journal Article |
Year |
2012 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
33 |
Issue |
15 |
Pages |
1980–1990 |
Keywords |
Structural pattern recognition; Graph embedding; Feature ranking; PCA; Graph classification |
Abstract |
Representing a graph with a feature vector is a common way of making statistical machine learning algorithms applicable to the domain of graphs. Such a transition from graphs to vectors is known as graphembedding. A key issue in graphembedding is to select a proper set of features in order to make the vectorial representation of graphs as strong and discriminative as possible. In this article, we propose features that are constructed out of frequencies of node label representatives. We first build a large set of features and then select the most discriminative ones according to different ranking criteria and feature transformation algorithms. On different classification tasks, we experimentally show that only a small significant subset of these features is needed to achieve the same classification rates as competing to state-of-the-art methods. |
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DAG |
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no |
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Admin @ si @ GVB2012b |
Serial |
1993 |
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Author |
Cristina Cañero; Petia Radeva |
Title |
Vesselness enhancement diffusion |
Type |
Journal Article |
Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
24 |
Issue |
16 |
Pages |
3141–3151 |
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Abstract |
IF: 0.809 |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ CaR2003 |
Serial |
371 |
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Author |
A. Sanfeliu; Juan J. Villanueva |
Title |
An approach of visual motion analysis |
Type |
Journal Article |
Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
26 |
Issue |
3 |
Pages |
355–368 |
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Abstract |
IF: 1.138 |
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no |
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ISE @ ise @ SaV2005 |
Serial |
561 |
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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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Notes |
ADAS;MILAB |
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no |
Call Number |
ADAS @ adas @ ASR2006 |
Serial |
643 |
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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 |
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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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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2009a |
Serial |
1153 |
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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 |
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no |
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DAG @ dag @ RBL2010 |
Serial |
1177 |
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Author |
Sergio Escalera; David Masip; Eloi Puertas; Petia Radeva; Oriol Pujol |
Title |
Online Error-Correcting Output Codes |
Type |
Journal Article |
Year |
2011 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
32 |
Issue |
3 |
Pages |
458-467 |
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Abstract |
IF JCR CCIA 1.303 2009 54/103
This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem independent codings one-versus-all and one-versus-one is introduced. Furthermore, two new codings are proposed, unbalanced online ECOC and a problem dependent online ECOC. This last online coding technique takes advantage of the problem data for minimizing the number of dichotomizers used in the ECOC framework while preserving a high accuracy. These techniques are validated on an online setting of 11 data sets from UCI database and applied to two real machine vision applications: traffic sign recognition and face recognition. As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier. |
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Elsevier |
Place of Publication |
North Holland |
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0167-8655 |
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MILAB;OR;HuPBA;MV |
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no |
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Admin @ si @ EMP2011 |
Serial |
1714 |
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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 |
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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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0167-8655 |
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DAG |
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no |
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DAG @ dag @ FVS2009a |
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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 |
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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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0167-8655 |
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ADAS |
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ADAS @ adas @ DoS2009a |
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1115 |
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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 @ dag @ RaV2006a |
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635 |
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Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
Title |
Augmenting Video Surveillance Footage with Virtual Agents for Incremental Event Evaluation |
Type |
Journal Article |
Year |
2011 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
Volume |
32 |
Issue |
6 |
Pages |
878–889 |
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The fields of segmentation, tracking and behavior analysis demand for challenging video resources to test, in a scalable manner, complex scenarios like crowded environments or scenes with high semantics. Nevertheless, existing public databases cannot scale the presence of appearing agents, which would be useful to study long-term occlusions and crowds. Moreover, creating these resources is expensive and often too particularized to specific needs. We propose an augmented reality framework to increase the complexity of image sequences in terms of occlusions and crowds, in a scalable and controllable manner. Existing datasets can be increased with augmented sequences containing virtual agents. Such sequences are automatically annotated, thus facilitating evaluation in terms of segmentation, tracking, and behavior recognition. In order to easily specify the desired contents, we propose a natural language interface to convert input sentences into virtual agent behaviors. Experimental tests and validation in indoor, street, and soccer environments are provided to show the feasibility of the proposed approach in terms of robustness, scalability, and semantics. |
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Elsevier |
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ISE |
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Admin @ si @ FBR2011b |
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1723 |
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