| Records |
| 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 |
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no |
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DAG @ dag @ RPS2010 |
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1290 |
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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 |
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1993 |
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| Author |
Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias |
| Title |
Understanding trained CNNs by indexing neuron selectivity |
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Journal Article |
| Year |
2020 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
136 |
Issue |
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Pages |
318-325 |
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The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understanding of the representations they build and how these representations are organized. To help understanding these issues, we propose to describe the activity of individual neurons by their Neuron Feature visualization and quantify their inherent selectivity with two specific properties. We explore selectivity indexes for: an image feature (color); and an image label (class membership). Our contribution is a framework to seek or classify neurons by indexing on these selectivity properties. It helps to find color selective neurons, such as a red-mushroom neuron in layer Conv4 or class selective neurons such as dog-face neurons in layer Conv5 in VGG-M, and establishes a methodology to derive other selectivity properties. Indexing on neuron selectivity can statistically draw how features and classes are represented through layers in a moment when the size of trained nets is growing and automatic tools to index neurons can be helpful. |
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CIC; 600.087; 600.140; 600.118 |
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Admin @ si @ RVL2019 |
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3310 |
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| Author |
A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva |
| Title |
Topological principal component analysis for face encoding and recognition |
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Journal Article |
| Year |
2001 |
Publication |
Pattern Recognition Letters |
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PRL |
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22 |
Issue |
6-7 |
Pages |
769–776 |
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IF: 0.552 |
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ADAS;OR;MV |
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ADAS @ adas @ PVL2001 |
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155 |
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| Author |
Jaume Amores; Petia Radeva |
| Title |
Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
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Journal Article |
| Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
26 |
Issue |
11 |
Pages |
1720–1731 |
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IF: 1.138 |
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ADAS;MILAB |
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ADAS @ adas @ AmR2005b |
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592 |
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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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ADAS @ adas @ ASR2006 |
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643 |
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| Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
| Title |
Multispectral Piecewise Planar Stereo using Manhattan-World Assumption |
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Journal Article |
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2013 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
34 |
Issue |
1 |
Pages |
52-61 |
| Keywords |
Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images |
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This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework. |
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ADAS; 600.054; 600.055; 605.203 |
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Admin @ si @ BLS2013 |
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2245 |
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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 |
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Journal Article |
| Year |
2007 |
Publication |
Pattern Recognition Letters |
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PRL |
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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 |
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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no |
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ADAS @ adas @ DoS2009a |
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1115 |
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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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IF: 1.138 |
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ISE @ ise @ SaV2005 |
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561 |
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