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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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| Notes | MILAB; CIC; HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ OtP2006 | Serial | 658 | ||
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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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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ DoS2007c | Serial | 877 | ||
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| Author | Bogdan Raducanu; Jordi Vitria | ||||
| Title | Learning to Learn: From Smarts Machines to Intelligent Machines | Type | Journal | ||
| Year | 2008 | Publication | Patter Recognition Letters | Abbreviated Journal |
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| Volume | 29 | Issue | 8 | Pages | 1024–1032 |
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaV2008a | Serial | 950 | ||
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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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| 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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| Publisher | Elsevier Science Inc. | Place of Publication | Editor | ||
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| ISSN | 0167-8655 | ISBN | Medium | ||
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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 |
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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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| Publisher | Elsevier Science Inc. | Place of Publication | Editor | ||
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| ISSN | 0167-8655 | ISBN | Medium | ||
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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 |
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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 | 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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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RBL2010 | Serial | 1177 | ||
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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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| Notes | HuPBA; DAG; MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EFP2009a | Serial | 1180 | ||
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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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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | 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 |
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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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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2010e | Serial | 1338 | ||
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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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| Publisher | Elsevier Science Inc. | Place of Publication | New York, NY, USA | Editor | |
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| ISSN | 0167-8655 | ISBN | Medium | ||
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| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GiR2006 | Serial | 1529 | ||
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| Author | Josep Llados; Horst Bunke; Enric Marti | ||||
| Title | Finding rotational symmetries by cyclic string matching | Type | Journal Article | ||
| Year | 1997 | Publication | Pattern recognition letters | Abbreviated Journal |
PRL |
| Volume | 18 | Issue | 14 | Pages | 1435-1442 |
| Keywords | Rotational symmetry; Reflectional symmetry; String matching | ||||
| Abstract | Symmetry is an important shape feature. In this paper, a simple and fast method to detect perfect and distorted rotational symmetries of 2D objects is described. The boundary of a shape is polygonally approximated and represented as a string. Rotational symmetries are found by cyclic string matching between two identical copies of the shape string. The set of minimum cost edit sequences that transform the shape string to a cyclically shifted version of itself define the rotational symmetry and its order. Finally, a modification of the algorithm is proposed to detect reflectional symmetries. Some experimental results are presented to show the reliability of the proposed algorithm | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | DAG;IAM; | Approved | no | ||
| Call Number | IAM @ iam @ LBM1997a | Serial | 1562 | ||
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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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| Publisher | Elsevier Science Inc. | Place of Publication | New York, NY, USA | Editor | |
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| ISSN | 0167-8655 | ISBN | Medium | ||
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| Notes | DAG; IAM | Approved | no | ||
| Call Number | IAM @ iam @ VAM2003 | Serial | 1653 | ||
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| Author | Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Xavier Roca | ||||
| Title | Efficient Discriminative Multiresolution Cascade for Real-Time Human Detection Applications | Type | Journal Article | ||
| Year | 2011 | Publication | Pattern Recognition Letters | Abbreviated Journal |
PRL |
| Volume | 32 | Issue | 13 | Pages | 1581-1587 |
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| Abstract | Human detection is fundamental in many machine vision applications, like video surveillance, driving assistance, action recognition and scene understanding. However in most of these applications real-time performance is necessary and this is not achieved yet by current detection methods.
This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a linear Support Vector Machine (SVM) composed of HOG features at different resolutions, from coarse at the first level to fine at the last one. In contrast to previous methods, our approach uses a non-uniform stride of the sliding window that is defined by the feature resolution and allows the detection to be incrementally refined as going from coarse-to-fine resolution. In this way, the speed-up of the cascade is not only due to the fewer number of features computed at the first levels of the cascade, but also to the reduced number of windows that need to be evaluated at the coarse resolution. Experimental results show that our method reaches a detection rate comparable with the state-of-the-art of detectors based on HOG features, while at the same time the detection search is up to 23 times faster. |
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ PGB2011a | Serial | 1707 | ||
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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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| Publisher | Elsevier | Place of Publication | North Holland | Editor | |
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| ISSN | 0167-8655 | ISBN | Medium | ||
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| Notes | MILAB;OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ EMP2011 | Serial | 1714 | ||
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