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Author Paula Fritzsche; C.Roig; Ana Ripoll; Emilio Luque; Aura Hernandez-Sabate
Title A Performance Prediction Methodology for Data-dependent Parallel Applications Type Conference Article
Year 2006 Publication Proceedings of the IEEE International Conference on Cluster Computing Abbreviated Journal
Volume Issue Pages (up) 1-8
Keywords
Abstract The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both deterministic applications and non-deterministic applications. In particular, the performance prediction of data dependent programs is an extremely challenging problem because for a specific issue the input datasets may cause different execution times. Generally, a parallel application is characterized as a collection of tasks and their interrelations. If the application is time-critical it is not enough to work with only one value per task, and consequently knowledge of the distribution of task execution times is crucial. The development of a new prediction methodology to estimate the performance of data-dependent parallel applications is the primary target of this study. This approach makes it possible to evaluate the parallel performance of an application without the need of implementation. A real data-dependent arterial structure detection application model is used to apply the methodology proposed. The predicted times obtained using the new methodology for genuine datasets are compared with predicted times that arise from using only one execution value per task. Finally, the experimental study shows that the new methodology generates more precise predictions.
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 Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ FRR2006 Serial 1497
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Author Jaume Garcia; Francesc Carreras; Sandra Pujades; Debora Gil
Title Regional motion patterns for the Left Ventricle function assessment Type Conference Article
Year 2008 Publication Proc. 19th Int. Conf. Pattern Recognition ICPR 2008 Abbreviated Journal
Volume Issue Pages (up) 1-4
Keywords
Abstract Regional scores (e.g. strain, perfusion) of the Left Ventricle (LV) functionality are playing an increasing role in the diagnosis of cardiac diseases. A main limitation is the lack of normality models for complementary scores oriented to assessment of the LV integrity. This paper introduces an original framework based on a parametrization of the LV domain, which allows comparison across subjects of local physiological measures of different nature. We compute regional normality patterns in a feature space characterizing the LV function. We show the consistency of the model for the regional motion on healthy and hypokinetic pathological cases
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 Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ GCP2008 Serial 1510
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa Type Conference Article
Year 2003 Publication Proceedings of Pattern Recognition in Information Systems Abbreviated Journal
Volume Issue Pages (up) 1-13
Keywords
Abstract
Address Angers, France
Corporate Author Thesis
Publisher ICEIS Press Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 972-98816-3-4 Medium
Area Expedition Conference PRIS'03
Notes DAG;IAM; Approved no
Call Number IAM @ iam @ LVS2003 Serial 1576
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Author Enric Marti; Ferran Poveda; Antoni Gurgui; Debora Gil
Title Aprendizaje Basado en Proyectos en Ingeniería Informática. Resultados y reflexiones de seis años de experiencia Type Miscellaneous
Year 2011 Publication Actas del Simposio-Taller JENUI 2011 Abbreviated Journal
Volume Issue Pages (up) 1-8
Keywords
Abstract In this workshop a 6 years experience in Project Based Learning (PBL) in Computer Graphics, Computer Engineering course at the Autonomous University of Barcelona (UAB) is presented. We use a Moodle environment suited to manage the documentation generated in PBL. The course is organized by means of two alternative routes: a classic itinerary of lectures and test-based evaluation and another with PBL. In the PBL itinerary we explain the organization in teamgroups, homework tutoring and monitoring and evaluation guidelines for students. We provide some of the work done by students, and the results of assessment surveys carried out to students during these years. We report the evolution of our PBL itinerary in terms of, both, organization and student surveys.
The workshop aims at discussing about on the advantages and disadvantages of using these active methodologies in technical degrees such as computer engineering, in order to debate about the most suitable way of organizing PBL and assessing students learning rate.
Address Sevilla, Spain
Corporate Author Thesis
Publisher Place of Publication Editor
Language spanish Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-694-5440-4 Medium
Area Expedition Conference JENUI
Notes IAM Approved no
Call Number IAM @ iam @ MPG2011 Serial 1584
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Author H. Emrah Tasli; Cevahir Çigla; Theo Gevers; A. Aydin Alatan
Title Super pixel extraction via convexity induced boundary adaptation Type Conference Article
Year 2013 Publication 14th IEEE International Conference on Multimedia and Expo Abbreviated Journal
Volume Issue Pages (up) 1-6
Keywords
Abstract This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iteratively by assigning boundary pixels to the most similar neighboring super-pixels. At each iteration, super-pixel regions are updated and hence progressively converging to compact pixel groups. Experimental results with state-of-the-art comparisons, validate the performance of the proposed technique in terms of both accuracy and speed.
Address San Jose; USA; July 2013
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 1945-7871 ISBN Medium
Area Expedition Conference ICME
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ TÇG2013 Serial 2367
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Author Petia Radeva; Jordi Vitria; Fernando Vilariño; Panagiota Spyridonos; Fernando Azpiroz; Juan Malagelada; Fosca de Iorio; Anna Accarino
Title Cascade analysis for intestinal contraction detection Type Patent
Year 2009 Publication US 2009/0284589 A1 Abbreviated Journal USPO
Volume Issue Pages (up) 1-25
Keywords
Abstract A method and system cascade analysisi for intestinal contraction detection is provided by extracting from image frames captured in-vivo. The method and system also relate to the detection of turbid liquids in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including a field of view obstructed by turbid media, and more particulary, to extraction of image data obstructed by turbid media.
Address
Corporate Author US Patent Office Thesis
Publisher US Patent Office Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB; OR; MV;SIAI Approved no
Call Number IAM @ iam @ RVV2009 Serial 1700
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Author Maria Salamo; Sergio Escalera
Title Increasing Retrieval Quality in Conversational Recommenders Type Journal Article
Year 2011 Publication IEEE Transactions on Knowledge and Data Engineering Abbreviated Journal TKDE
Volume 99 Issue Pages (up) 1-1
Keywords
Abstract IF JCR CCIA 2.286 2009 24/103
JCR Impact Factor 2010: 1.851
A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing specific preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efficiently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisfied critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology significantly improves recommendation efficiency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches
Address
Corporate Author Thesis
Publisher IEEE Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1041-4347 ISBN Medium
Area Expedition Conference
Notes MILAB; HuPBA Approved no
Call Number Admin @ si @ SaE2011 Serial 1713
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Author Jon Almazan; Ernest Valveny; Alicia Fornes
Title Deforming the Blurred Shape Model for Shape Description and Recognition Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages (up) 1-8
Keywords
Abstract This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Berlin Editor Jordi Vitria; Joao Miguel Raposo; Mario Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference IbPRIA
Notes DAG; Approved no
Call Number Admin @ si @ AVF2011 Serial 1732
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Author S. Chanda; Umapada Pal; Oriol Ramos Terrades
Title Word-Wise Thai and Roman Script Identification Type Journal
Year 2009 Publication ACM Transactions on Asian Language Information Processing Abbreviated Journal TALIP
Volume 8 Issue 3 Pages (up) 1-21
Keywords
Abstract In some Thai documents, a single text line of a printed document page may contain words of both Thai and Roman scripts. For the Optical Character Recognition (OCR) of such a document page it is better to identify, at first, Thai and Roman script portions and then to use individual OCR systems of the respective scripts on these identified portions. In this article, an SVM-based method is proposed for identification of word-wise printed Roman and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of a character group combining different character features obtained from structural shape, profile behavior, component overlapping information, topological properties, and water reservoir concept, etc. Based on the experiment on 10,000 data (words) we obtained 99.62% script identification accuracy from the proposed scheme.
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 1530-0226 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ CPR2009f Serial 1869
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Author H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent
Title Feature Selection Combining Genetic Algorithm and Adaboost Classifiers Type Conference Article
Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages (up) 1-4
Keywords
Abstract
Address Tampa, Florida
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 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number Admin @ si @ CRT2008 Serial 1872
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Author Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat
Title Histogram of radon transform. A useful descriptor for shape retrieval Type Conference Article
Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages (up) 1-4
Keywords
Abstract
Address Tampa, Florida
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 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number Admin @ si @ TRB2008 Serial 1876
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Author Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Xavier Jimenez ; Oscar Vilarroya; Petia Radeva
Title A fully-automatic caudate nucleus segmentation of brain MRI: Application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder Type Journal Article
Year 2011 Publication BioMedical Engineering Online Abbreviated Journal BEO
Volume 10 Issue 105 Pages (up) 1-23
Keywords Brain caudate nucleus; segmentation; MRI; atlas-based strategy; Graph Cut framework
Abstract Background
Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations.

Method
We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure.

Results
We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis.

Conclusion
CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.
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 1475-925X ISBN Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ ISH2011 Serial 1882
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Author David Geronimo; Antonio Lopez
Title Vision-based Pedestrian Protection Systems for Intelligent Vehicles Type Book Whole
Year 2014 Publication SpringerBriefs in Computer Science Abbreviated Journal
Volume Issue Pages (up) 1-114
Keywords Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users
Abstract Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented.
Address
Corporate Author Thesis
Publisher Springer Briefs in Computer Vision Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-4614-7986-4 Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number GeL2014 Serial 2325
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Author Jordi Roca; C. Alejandro Parraga; Maria Vanrell
Title Chromatic settings and the structural color constancy index Type Journal Article
Year 2013 Publication Journal of Vision Abbreviated Journal JV
Volume 13 Issue 4-3 Pages (up) 1-26
Keywords
Abstract Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects.
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 Medium
Area Expedition Conference
Notes CIC; 600.052; 600.051; 605.203 Approved no
Call Number Admin @ si @ RPV2013 Serial 2288
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Author David Vazquez
Title Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection Type Book Whole
Year 2013 Publication PhD Thesis, Universitat de Barcelona-CVC Abbreviated Journal
Volume 1 Issue 1 Pages (up) 1-105
Keywords Pedestrian Detection; Domain Adaptation
Abstract Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area.
Address Barcelona
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Barcelona Editor Antonio Lopez;Daniel Ponsa
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-940530-1-6 Medium
Area Expedition Conference
Notes adas Approved yes
Call Number ADAS @ adas @ Vaz2013 Serial 2276
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