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Author Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez
Title Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books Type Conference Article
Year 2016 Publication 15th international conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract Handwritten marriage licenses books have been used for centuries by ecclesiastical and secular institutions to register marriages. The information contained in these historical documents is useful for demography studies and
genealogical research, among others. Despite the generally simple structure of the text in these documents, automatic transcription and semantic information extraction is difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In previous
works we studied the use of category-based language models to both improve the automatic transcription accuracy and make easier the extraction of semantic information. Here we analyze the main causes of the semantic errors observed in previous results and apply a Grammatical Inference technique known as MGGI to improve the semantic accuracy of the language model obtained. Using this language model, full handwritten text recognition experiments have been carried out, with results supporting the interest of the proposed approach.
Address Shenzhen; China; October 2016
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 ICFHR
Notes DAG; 600.097; 602.006 Approved no
Call Number Admin @ si @ RFV2016 Serial 2909
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Author Iiris Lusi; Sergio Escalera; Gholamreza Anbarjafari
Title Human Head Pose Estimation on SASE database using Random Hough Regression Forests Type Conference Article
Year 2016 Publication 23rd International Conference on Pattern Recognition Workshops Abbreviated Journal
Volume 10165 Issue Pages
Keywords (up)
Abstract In recent years head pose estimation has become an important task in face analysis scenarios. Given the availability of high resolution 3D sensors, the design of a high resolution head pose database would be beneficial for the community. In this paper, Random Hough Forests are used to estimate 3D head pose and location on a new 3D head database, SASE, which represents the baseline performance on the new data for an upcoming international head pose estimation competition. The data in SASE is acquired with a Microsoft Kinect 2 camera, including the RGB and depth information of 50 subjects with a large sample of head poses, allowing us to test methods for real-life scenarios. We briefly review the database while showing baseline head pose estimation results based on Random Hough Forests.
Address Cancun; Mexico; December 2016
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICPRW
Notes HuPBA; Approved no
Call Number Admin @ si @ LEA2016b Serial 2910
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Author Xavier Baro; Sergio Escalera; Isabelle Guyon; Julio C. S. Jacques Junior; Lukasz Romaszko; Lisheng Sun; Sebastien Treguer; Evelyne Viegas
Title Coompetitions in machine learning: case studies Type Conference Article
Year 2016 Publication 30th Annual Conference on Neural Information Processing Systems Worshops Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract
Address Barcelona; Spain; December 2016
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 NIPSW
Notes HuPBA Approved no
Call Number Admin @ si @ BEG2016 Serial 2911
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Author Anastasios Doulamis; Nikolaos Doulamis; Marco Bertini; Jordi Gonzalez; Thomas B. Moeslund
Title Introduction to the Special Issue on the Analysis and Retrieval of Events/Actions and Workflows in Video Streams Type Journal Article
Year 2016 Publication Multimedia Tools and Applications Abbreviated Journal MTAP
Volume 75 Issue 22 Pages 14985-14990
Keywords (up)
Abstract
Address
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes ISE; HUPBA Approved no
Call Number Admin @ si @ DDB2016 Serial 2934
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Author Carles Sanchez; Debora Gil; T. Gache; N. Koufos; Marta Diez-Ferrer; Antoni Rosell
Title SENSA: a System for Endoscopic Stenosis Assessment Type Conference Article
Year 2016 Publication 28th Conference of the international Society for Medical Innovation and Technology Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract Documenting the severity of a static or dynamic Central Airway Obstruction (CAO) is crucial to establish proper diagnosis and treatment, predict possible treatment effects and better follow-up the patients. The subjective visual evaluation of a stenosis during video-bronchoscopy still remains the most common way to assess a CAO in spite of a consensus among experts for a need to standardize all calculations [1].
The Computer Vision Center in cooperation with the «Hospital de Bellvitge», has developed a System for Endoscopic Stenosis Assessment (SENSA), which computes CAO directly by analyzing standard bronchoscopic data without the need of using other imaging tecnologies.
Address Rotterdam; The Netherlands; October 2016
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 SMIT
Notes IAM; Approved no
Call Number Admin @ si @ SGG2016 Serial 2942
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Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
Title Spotting Symbol over Graphical Documents Via Sparsity in Visual Vocabulary Type Book Chapter
Year 2016 Publication Recent Trends in Image Processing and Pattern Recognition Abbreviated Journal
Volume 709 Issue Pages
Keywords (up)
Abstract
Address
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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 RTIP2R
Notes DAG Approved no
Call Number Admin @ si @ HTR2016 Serial 2956
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Author Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Cubero Noelia; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell
Title Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation Type Journal Article
Year 2016 Publication Chest Journal Abbreviated Journal CHEST
Volume 150 Issue 4 Pages 1003A
Keywords (up)
Abstract
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; 600.096; 600.075 Approved no
Call Number Admin @ si @ DGC2016 Serial 3099
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Author Maria Salamo; Inmaculada Rodriguez; Maite Lopez; Anna Puig; Simone Balocco; Mariona Taule
Title Recurso docente para la atención de la diversidad en el aula mediante la predicción de notas Type Journal
Year 2016 Publication ReVision Abbreviated Journal
Volume 9 Issue 1 Pages
Keywords (up) Aprendizaje automatico; Sistema de prediccion de notas; Herramienta docente
Abstract Desde la implantación del Espacio Europeo de Educación Superior (EEES) en los diferentes grados, se ha puesto de manifiesto la necesidad de utilizar diversos mecanismos que permitan tratar la diversidad en el aula, evaluando automáticamente y proporcionando una retroalimentación rápida tanto al alumnado como al profesorado sobre la evolución de los alumnos en una asignatura. En este artículo se presenta la evaluación de la exactitud en las predicciones de GRADEFORESEER, un recurso docente para la predicción de notas basado en técnicas de aprendizaje automático que permite evaluar la evolución del alumnado y estimar su nota final al terminar el curso. Este recurso se ha complementado con una interfaz de usuario para el profesorado que puede ser usada en diferentes plataformas software (sistemas operativos) y en cualquier asignatura de un grado en la que se utilice evaluación continuada. Además de la descripción del recurso, este artículo presenta los resultados obtenidos al aplicar el sistema de predicción en cuatro asignaturas de disciplinas distintas: Programación I (PI), Diseño de Software (DSW) del grado de Ingeniería Informática, Tecnologías de la Información y la Comunicación (TIC) del grado de Lingüística y la asignatura Fundamentos de Tecnología (FDT) del grado de Información y Documentación, todas ellas impartidas en la Universidad de Barcelona.

La capacidad predictiva se ha evaluado de forma binaria (aprueba o no) y según un criterio de rango (suspenso, aprobado, notable o sobresaliente), obteniendo mejores predicciones en los resultados evaluados de forma binaria.
Address
Corporate Author Thesis
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Area Expedition Conference
Notes MILAB; Approved no
Call Number Admin @ si @ SRL2016 Serial 2820
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Author C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi
Title Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM Type Journal Article
Year 2016 Publication Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization Abbreviated Journal CMBBE
Volume 4 Issue 5 Pages 265-280
Keywords (up) ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation
Abstract In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach.
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 2168-1163 ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ BBS2016 Serial 2449
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Author Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas
Title A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention Type Conference Article
Year 2016 Publication AutoML Workshop Abbreviated Journal
Volume Issue 1 Pages 1-8
Keywords (up) AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning
Abstract The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML.
Address New York; USA; June 2016
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 ICML
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ GCE2016 Serial 2769
Permanent link to this record
 
 
Author Eugenio Alcala; Laura Sellart; Vicenc Puig; Joseba Quevedo; Jordi Saludes; David Vazquez; Antonio Lopez
Title Comparison of two non-linear model-based control strategies for autonomous vehicles Type Conference Article
Year 2016 Publication 24th Mediterranean Conference on Control and Automation Abbreviated Journal
Volume Issue Pages 846-851
Keywords (up) Autonomous Driving; Control
Abstract This paper presents the comparison of two nonlinear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first order sliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation.
Address Athens; Greece; June 2016
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 MED
Notes ADAS; 600.085; 600.082; 600.076 Approved no
Call Number ADAS @ adas @ ASP2016 Serial 2750
Permanent link to this record
 
 
Author Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez
Title Embedded real-time stereo estimation via Semi-Global Matching on the GPU Type Conference Article
Year 2016 Publication 16th International Conference on Computational Science Abbreviated Journal
Volume 80 Issue Pages 143-153
Keywords (up) Autonomous Driving; Stereo; CUDA; 3d reconstruction
Abstract Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy-efficient GPU devices. Our design runs on a Tegra X1 at 41 frames per second for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method.
Address San Diego; CA; USA; June 2016
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 ICCS
Notes ADAS; 600.085; 600.082; 600.076 Approved no
Call Number ADAS @ adas @ HCE2016a Serial 2740
Permanent link to this record
 
 
Author Jean-Pascal Jacob; Mariella Dimiccoli; Lionel Moisan
Title Active skeleton for bacteria modeling Type Journal Article
Year 2016 Publication Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization Abbreviated Journal CMBBE
Volume 5 Issue 4 Pages 274-286
Keywords (up) Bacteria modelling; medial axis; active contours; active skeleton; shape contraints
Abstract The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modeling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness, orientation), an improved boundary accuracy in noisy images, and a natural bacteria-centered coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimizing an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modeling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at this http URL
Address
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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 Approved no
Call Number Admin @ si @ JDM2016 Serial 2711
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Author Victor Ponce; Baiyu Chen; Marc Oliu; Ciprian Corneanu; Albert Clapes; Isabelle Guyon; Xavier Baro; Hugo Jair Escalante; Sergio Escalera
Title ChaLearn LAP 2016: First Round Challenge on First Impressions – Dataset and Results Type Conference Article
Year 2016 Publication 14th European Conference on Computer Vision Workshops Abbreviated Journal
Volume Issue Pages
Keywords (up) Behavior Analysis; Personality Traits; First Impressions
Abstract This paper summarizes the ChaLearn Looking at People 2016 First Impressions challenge data and results obtained by the teams in the rst round of the competition. The goal of the competition was to automatically evaluate ve \apparent“ personality traits (the so-called \Big Five”) from videos of subjects speaking in front of a camera, by using human judgment. In this edition of the ChaLearn challenge, a novel data set consisting of 10,000 shorts clips from YouTube videos has been made publicly available. The ground truth for personality traits was obtained from workers of Amazon Mechanical Turk (AMT). To alleviate calibration problems between workers, we used pairwise comparisons between videos, and variable levels were reconstructed by tting a Bradley-Terry-Luce model with maximum likelihood. The CodaLab open source
platform was used for submission of predictions and scoring. The competition attracted, over a period of 2 months, 84 participants who are grouped in several teams. Nine teams entered the nal phase. Despite the diculty of the task, the teams made great advances in this round of the challenge.
Address Amsterdam; The Netherlands; October 2016
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 ECCVW
Notes HuPBA;MV; 600.063 Approved no
Call Number Admin @ si @ PCP2016 Serial 2828
Permanent link to this record
 
 
Author Carles Sanchez; Debora Gil; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell
Title Navigation Path Retrieval from Videobronchoscopy using Bronchial Branches Type Conference Article
Year 2016 Publication 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops Abbreviated Journal
Volume 9401 Issue Pages 62-70
Keywords (up) Bronchoscopy navigation; Lumen center; Brochial branches; Navigation path; Videobronchoscopy
Abstract Bronchoscopy biopsy can be used to diagnose lung cancer without risking complications of other interventions like transthoracic needle aspiration. During bronchoscopy, the clinician has to navigate through the bronchial tree to the target lesion. A main drawback is the difficulty to check whether the exploration is following the correct path. The usual guidance using fluoroscopy implies repeated radiation of the clinician, while alternative systems (like electromagnetic navigation) require specific equipment that increases intervention costs. We propose to compute the navigated path using anatomical landmarks extracted from the sole analysis of videobronchoscopy images. Such landmarks allow matching the current exploration to the path previously planned on a CT to indicate clinician whether the planning is being correctly followed or not. We present a feasibility study of our landmark based CT-video matching using bronchoscopic videos simulated on a virtual bronchoscopy interactive interface.
Address Quebec; Canada; September 2016
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAIW
Notes IAM; MV; 600.060; 600.075 Approved no
Call Number Admin @ si @ SGB2016 Serial 2885
Permanent link to this record