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| Author | Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone | ||||
| Title | Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework | Type | Journal Article | ||
Year  |
2009 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 31 | Issue | 9 | Pages | 1630–1644 |
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| Abstract | The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. | ||||
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| ISSN | 0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RVT2009 | Serial | 1220 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach | Type | Journal Article | ||
| Year |
2009 | Publication | International Journal of Electronic Commerce | Abbreviated Journal | |
| Volume | 14 | Issue | 1 | Pages | 89-108 |
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| Abstract | The paper presents a factorization-based approach to make predictions in recommender systems. These systems are widely used in electronic commerce to help customers find products according to their preferences. Taking into account the customer's ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the system. The proposed factorization-based approach uses all the information provided to compute the predicted ratings, in the same way as approaches based on Singular Value Decomposition (SVD). The main advantage of this technique versus SVD-based approaches is that it can deal with missing data. It also has a smaller computational cost. Experimental results with public data sets are provided to show that the proposed adapted factorization approach gives better predicted ratings than a widely used SVD-based approach. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1086-4415 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ JSL2009b | Serial | 1237 | ||
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| Author | Arnau Ramisa; Adriana Tapus; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras | ||||
| Title | Robust Vision-Based Localization using Combinations of Local Feature Regions Detectors | Type | Journal Article | ||
| Year |
2009 | Publication | Autonomous Robots | Abbreviated Journal | AR |
| Volume | 27 | Issue | 4 | Pages | 373-385 |
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| Abstract | This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°.
In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization. |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0929-5593 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RTA2009 | Serial | 1245 | ||
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| Author | Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. M. Ferre; Petia Radeva | ||||
| Title | Fast Rigid Registration of Vascular Structures in IVUS Sequences | Type | Journal Article | ||
| Year |
2009 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | |
| Volume | 13 | Issue | 6 | Pages | 106-1011 |
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| Abstract | Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns 3.16 frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ GPL2009 | Serial | 1250 | ||
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| Author | Fosca De Iorio; Carolina Malagelada; Fernando Azpiroz; M. Maluenda; C. Violanti; Laura Igual; Jordi Vitria; Juan R. Malagelada | ||||
| Title | Intestinal motor activity, endoluminal motion and transit | Type | Journal Article | ||
| Year |
2009 | Publication | Neurogastroenterology & Motility | Abbreviated Journal | NEUMOT |
| Volume | 21 | Issue | 12 | Pages | 1264–e119 |
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| Abstract | A programme for evaluation of intestinal motility has been recently developed based on endoluminal image analysis using computer vision methodology and machine learning techniques. Our aim was to determine the effect of intestinal muscle inhibition on wall motion, dynamics of luminal content and transit in the small bowel. Fourteen healthy subjects ingested the endoscopic capsule (Pillcam, Given Imaging) in fasting conditions. Seven of them received glucagon (4.8 microg kg(-1) bolus followed by a 9.6 microg kg(-1) h(-1) infusion during 1 h) and in the other seven, fasting activity was recorded, as controls. This dose of glucagon has previously shown to inhibit both tonic and phasic intestinal motor activity. Endoluminal image and displacement was analyzed by means of a computer vision programme specifically developed for the evaluation of muscular activity (contractile and non-contractile patterns), intestinal contents, endoluminal motion and transit. Thirty-minute periods before, during and after glucagon infusion were analyzed and compared with equivalent periods in controls. No differences were found in the parameters measured during the baseline (pretest) periods when comparing glucagon and control experiments. During glucagon infusion, there was a significant reduction in contractile activity (0.2 +/- 0.1 vs 4.2 +/- 0.9 luminal closures per min, P < 0.05; 0.4 +/- 0.1 vs 3.4 +/- 1.2% of images with radial wrinkles, P < 0.05) and a significant reduction of endoluminal motion (82 +/- 9 vs 21 +/- 10% of static images, P < 0.05). Endoluminal image analysis, by means of computer vision and machine learning techniques, can reliably detect reduced intestinal muscle activity and motion. | ||||
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| Notes | OR;MILAB;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DMA2009 | Serial | 1251 | ||
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| Author | Oriol Pujol; David Masip | ||||
| Title | Geometry-Based Ensembles: Toward a Structural Characterization of the Classification Boundary | Type | Journal Article | ||
| Year |
2009 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 31 | Issue | 6 | Pages | 1140–1146 |
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| Abstract | This article introduces a novel binary discriminative learning technique based on the approximation of the non-linear decision boundary by a piece-wise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points – points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and non-linear behavior is obtained. The simplicity of the method allows its extension to cope with some of nowadays machine learning challenges, such as online learning, large scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database. Finally, we apply our technique in online and large scale scenarios, and in six real life computer vision and pattern recognition problems: gender recognition, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease severity detection, clef classification and action recognition using a 3D accelerometer data. The results are promising and this paper opens a line of research that deserves further attention | ||||
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| Notes | OR;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PuM2009 | Serial | 1252 | ||
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| Author | Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva | ||||
| Title | Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes | Type | Journal Article | ||
| Year |
2009 | Publication | Journal of Signal Processing Systems | Abbreviated Journal | |
| Volume | 55 | Issue | 1-3 | Pages | 35–47 |
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| Abstract | Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1939-8018 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPM2009 | Serial | 1258 | ||
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| Author | Aura Hernandez-Sabate; Debora Gil;Eduard Fernandez-Nofrerias;Petia Radeva; Enric Marti | ||||
| Title | Approaching Artery Rigid Dynamics in IVUS | Type | Journal Article | ||
| Year |
2009 | Publication | IEEE Transactions on Medical Imaging | Abbreviated Journal | TMI |
| Volume | 28 | Issue | 11 | Pages | 1670-1680 |
| Keywords | Fourier analysis; intravascular ultrasound (IVUS) dynamics; longitudinal motion; quality measures; tissue deformation. | ||||
| Abstract | Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0278-0062 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM; MILAB | Approved | no | ||
| Call Number | IAM @ iam @ HGF2009 | Serial | 1545 | ||
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| Author | Misael Rosales; Petia Radeva; Oriol Rodriguez-Leor; Debora Gil | ||||
| Title | Modelling of image-catheter motion for 3-D IVUS | Type | Journal Article | ||
| Year |
2009 | Publication | Medical image analysis | Abbreviated Journal | MIA |
| Volume | 13 | Issue | 1 | Pages | 91-104 |
| Keywords | Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier | ||||
| Abstract | Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS. | ||||
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| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ RRR2009 | Serial | 1646 | ||
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| Author | Fernando Vilariño; Stephan Ameling; Gerard Lacey; Stephen Patchett; Hugh Mulcahy | ||||
| Title | Eye Tracking Search Patterns in Expert and Trainee Colonoscopists: A Novel Method of Assessing Endoscopic Competency? | Type | Journal Article | ||
| Year |
2009 | Publication | Gastrointestinal Endoscopy | Abbreviated Journal | GI |
| Volume | 69 | Issue | 5 | Pages | 370 |
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| Area | 800 | Expedition | Conference | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number | fernando @ fernando @ | Serial | 2420 | ||
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| Author | Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño | ||||
| Title | Texture-based Polyp Detection in Colonoscopy | Type | Journal Article | ||
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2009 | Publication | Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN | Abbreviated Journal | |
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| Area | 800 | Expedition | Conference | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number | fernando @ fernando @ | Serial | 2428 | ||
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| Author | Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva | ||||
| Title | On Tracking Inside Groups | Type | Journal Article | ||
| Year |
2010 | Publication | Machine Vision and Applications | Abbreviated Journal | MVA |
| Volume | 21 | Issue | 2 | Pages | 113–127 |
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| Abstract | This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ RGP2010 | Serial | 1158 | ||
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| Author | Marçal Rusiñol; Josep Llados; Gemma Sanchez | ||||
| Title | Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings | Type | Journal Article | ||
| Year |
2010 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
| Volume | 13 | Issue | 3 | Pages | 321-331 |
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| Abstract | In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-7541 | ISBN | Medium | ||
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| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RLS2010 | Serial | 1165 | ||
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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 | Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez | ||||
| Title | Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences | Type | Journal Article | ||
| Year |
2010 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
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| Abstract | Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes. |
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| ISSN | 1110-8657 | ISBN | Medium | ||
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ MRR2010 | Serial | 1208 | ||
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