|   | 
Details
   web
Records
Author Eloi Puertas; Sergio Escalera; Oriol Pujol
Title Multi-Class Multi-Scale Stacked Sequential Learning Type Conference Article
Year 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 197-206
Keywords
Abstract
Address Napoles, Italy
Corporate Author Thesis
Publisher Springer Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference MCS
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ PEP2011b Serial 1772
Permanent link to this record
 

 
Author Oscar Amoros; Sergio Escalera; Anna Puig
Title Adaboost GPU-based Classifier for Direct Volume Rendering Type Conference Article
Year 2011 Publication International Conference on Computer Graphics Theory and Applications Abbreviated Journal
Volume Issue Pages 215-219
Keywords
Abstract In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges.
Address Algarve, Portugal
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference GRAPP
Notes MILAB; HuPBA Approved no
Call Number Admin @ si @ AEP2011 Serial 1774
Permanent link to this record
 

 
Author Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras
Title The IIIA30 MObile Robot Object Recognition Datset Type Conference Article
Year 2011 Publication 11th Portuguese Robotics Open Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones.
Address Lisboa
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference Robotica
Notes RV;ADAS Approved no
Call Number Admin @ si @ RAV2011 Serial 1777
Permanent link to this record
 

 
Author Joan M. Nuñez
Title Computer vision techniques for characterization of finger joints in X-ray image Type Report
Year 2011 Publication CVC Technical Report Abbreviated Journal
Volume 165 Issue Pages
Keywords Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge
Abstract Rheumatoid arthritis (RA) is an autoimmune inflammatory type of arthritis which mainly affects hands on its first stages. Though it is a chronic disease and there is no cure for it, treatments require an accurate assessment of illness evolution. Such assessment is based on evaluation of hand X-ray images by using one of the several available semi-quantitative methods. This task requires highly trained medical personnel. That is why the automation of the assessment would allow professionals to save time and effort. Two stages are involved in this task. Firstly, the joint detection, afterwards, the joint characterization. Unlike the little existing previous work, this contribution clearly separates those two stages and sets the foundations of a modular assessment system focusing on the characterization stage. A hand joint dataset is created and an accurate data analysis is achieved in order to identify relevant features. Since the sclerosis and the lower bone were decided to be the most important features, different computer vision techniques were used in order to develop a detector system for both of them. Joint space width measures are provided and their correlation with Sharp-Van der Heijde is verified
Address Bellaterra (Barcelona)
Corporate Author Computer Vision Center Thesis Master's thesis
Publisher Place of Publication Editor Dr. Fernando Vilariño and Dra. Debora Gil
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference
Notes MV;IAM; Approved no
Call Number IAM @ iam @ Nuñ2011 Serial 1795
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa
Title Implicit B-Spline Fitting Using the 3L Algorithm Type Conference Article
Year 2011 Publication 18th IEEE International Conference on Image Processing Abbreviated Journal
Volume Issue Pages 893-896
Keywords
Abstract
Address Brussels, Belgium
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference ICIP
Notes ADAS Approved no
Call Number Admin @ si @ RoS2011a; ADAS @ adas @ Serial 1782
Permanent link to this record
 

 
Author Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera
Title Analisis de la Expresion Oral y Gestual en Proyectos Fin de Carrera Via un Sistema de Vision Artificial Type Miscellaneous
Year 2011 Publication Revista electronica de la asociacion de enseñantes universitarios de la informatica AENUI Abbreviated Journal ReVision
Volume 4 Issue 1 Pages 8-18
Keywords
Abstract La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1989-1199 ISBN (up) Medium
Area Expedition Conference
Notes MILAB;HuPBA;MV Approved no
Call Number Admin @ si @ PGB2011c Serial 1783
Permanent link to this record
 

 
Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Josep Llados; Petia Radeva
Title Circular Blurred Shape Model for Multiclass Symbol Recognition Type Journal Article
Year 2011 Publication IEEE Transactions on Systems, Man and Cybernetics (Part B) (IEEE) Abbreviated Journal TSMCB
Volume 41 Issue 2 Pages 497-506
Keywords
Abstract In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1083-4419 ISBN (up) Medium
Area Expedition Conference
Notes MILAB; DAG;HuPBA Approved no
Call Number Admin @ si @ EFP2011 Serial 1784
Permanent link to this record
 

 
Author Javier Vazquez
Title Colour Constancy in Natural Through Colour Naming and Sensor Sharpening Type Book Whole
Year 2011 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation.
The implementation of this selection criterion strongly relies on the use of a diagonal
model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D.
Several research lines still remain open. One natural extension would be to measure the
effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Maria Vanrell;Graham D. Finlayson
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference
Notes CIC Approved no
Call Number Admin @ si @ Vaz2011a Serial 1785
Permanent link to this record
 

 
Author Ferran Diego
Title Probabilistic Alignment of Video Sequences Recorded by Moving Cameras Type Book Whole
Year 2011 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Video alignment consists of integrating multiple video sequences recorded independently into a single video sequence. This means to register both in time (synchronize
frames) and space (image registration) so that the two videos sequences can be fused
or compared pixel–wise. In spite of being relatively unknown, many applications today may benefit from the availability of robust and efficient video alignment methods.
For instance, video surveillance requires to integrate video sequences that are recorded
of the same scene at different times in order to detect changes. The problem of aligning videos has been addressed before, but in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, most works rely
on restrictive assumptions which reduce its difficulty such as linear time correspondence or the knowledge of the complete trajectories of corresponding scene points on the images; to some extent, these assumptions limit the practical applicability of the solutions developed until now. In this thesis, we focus on the challenging problem of aligning sequences recorded at different times from independent moving cameras following similar but not coincident trajectories. More precisely, this thesis covers four studies that advance the state-of-the-art in video alignment. First, we focus on analyzing and developing a probabilistic framework for video alignment, that is, a principled way to integrate multiple observations and prior information. In this way, two different approaches are presented to exploit the combination of several purely visual features (image–intensities, visual words and dense motion field descriptor), and
global positioning system (GPS) information. Second, we focus on reformulating the
problem into a single alignment framework since previous works on video alignment
adopt a divide–and–conquer strategy, i.e., first solve the synchronization, and then
register corresponding frames. This also generalizes the ’classic’ case of fixed geometric transform and linear time mapping. Third, we focus on exploiting directly the
time domain of the video sequences in order to avoid exhaustive cross–frame search.
This provides relevant information used for learning the temporal mapping between
pairs of video sequences. Finally, we focus on adapting these methods to the on–line
setting for road detection and vehicle geolocation. The qualitative and quantitative
results presented in this thesis on a variety of real–world pairs of video sequences show that the proposed method is: robust to varying imaging conditions, different image
content (e.g., incoming and outgoing vehicles), variations on camera velocity, and
different scenarios (indoor and outdoor) going beyond the state–of–the–art. Moreover, the on–line video alignment has been successfully applied for road detection and
vehicle geolocation achieving promising results.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Joan Serrat
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ Die2011 Serial 1787
Permanent link to this record
 

 
Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados
Title Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 63-67
Keywords
Abstract In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts.
Address Beijing, China
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference ICDAR
Notes DAG;ADAS Approved no
Call Number Admin @ si @ RAT2011 Serial 1788
Permanent link to this record
 

 
Author Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes
Title Co-training for Handwritten Word Recognition Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 314-318
Keywords
Abstract To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition.
Address Beijing, China
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ FFB2011 Serial 1789
Permanent link to this record
 

 
Author Xavier Carrillo; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; Petia Radeva; Neus Salvatella; Oriol Pujol; J. Mauri; A. Bayes
Title Changes in Radial Artery Volume Assessed Using Intravascular Ultrasound: A Comparison of Two Vasodilator Regimens in Transradial Coronary Intervention Type Journal Article
Year 2011 Publication Journal of Invasive Cardiology Abbreviated Journal JOIC
Volume 23 Issue 10 Pages 401-404
Keywords radial; vasodilator treatment; percutaneous coronary intervention; IVUS; volumetric IVUS analysis
Abstract OBJECTIVES:
This study used intravascular ultrasound (IVUS) to evaluate radial artery volume changes after intraarterial administration of nitroglycerin and/or verapamil.
BACKGROUND:
Radial artery spasm, which is associated with radial artery size, is the main limitation of the transradial approach in percutaneous coronary interventions (PCI).
METHODS:
This prospective, randomized study compared the effect of two intra-arterial vasodilator regimens on radial artery volume: 0.2 mg of nitroglycerin plus 2.5 mg of verapamil (Group 1; n = 15) versus 2.5 mg of verapamil alone (Group 2; n = 15). Radial artery lumen volume was assessed using IVUS at two time points: at baseline (5 minutes after sheath insertion) and post-vasodilator (1 minute after drug administration). The luminal volume of the radial artery was computed using ECOC Random Fields (ECOC-RF), a technique used for automatic segmentation of luminal borders in longitudinal cut images from IVUS sequences.
RESULTS:
There was a significant increase in arterial lumen volume in both groups, with an increase from 451 ± 177 mm³ to 508 ± 192 mm³ (p = 0.001) in Group 1 and from 456 ± 188 mm³ to 509 ± 170 mm³ (p = 0.001) in Group 2. There were no significant differences between the groups in terms of absolute volume increase (58 mm³ versus 53 mm³, respectively; p = 0.65) or in relative volume increase (14% versus 20%, respectively; p = 0.69).
CONCLUSIONS:
Administration of nitroglycerin plus verapamil or verapamil alone to the radial artery resulted in similar increases in arterial lumen volume according to ECOC-RF IVUS measurements.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ CFC2011 Serial 1797
Permanent link to this record
 

 
Author Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne
Title Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans Type Conference Article
Year 2011 Publication In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Toronto, Canada
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference PIA
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ CPL2011 Serial 1798
Permanent link to this record
 

 
Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Petia Radeva; Jordi Vitria; Oriol Pujol
Title Minimal Design of Error-Correcting Output Codes Type Journal Article
Year 2011 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 33 Issue 6 Pages 693-702
Keywords Multi-class classification; Error-correcting output codes; Ensemble of classifiers
Abstract IF JCR CCIA 1.303 2009 54/103
The classification of large number of object categories is a challenging trend in the pattern recognition field. In literature, this is often addressed using an ensemble of classifiers. In this scope, the Error-correcting output codes framework has demonstrated to be a powerful tool for combining classifiers. However, most state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best minimal ECOC code configuration. The results over several public UCI datasets and different multi-class computer vision problems show that the proposed methodology obtains comparable (even better) results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0167-8655 ISBN (up) Medium
Area Expedition Conference
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BEB2011a Serial 1800
Permanent link to this record
 

 
Author Carlo Gatta; Eloi Puertas; Oriol Pujol
Title Multi-Scale Stacked Sequential Learning Type Journal Article
Year 2011 Publication Pattern Recognition Abbreviated Journal PR
Volume 44 Issue 10-11 Pages 2414-2416
Keywords Stacked sequential learning; Multiscale; Multiresolution; Contextual classification
Abstract One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN (up) Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ GPP2011 Serial 1802
Permanent link to this record