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Author Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva
Title (up) Adaptable image cuts for motility inspection using WCE Type Journal Article
Year 2013 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG
Volume 37 Issue 1 Pages 72-80
Keywords
Abstract The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.
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Area Expedition Conference
Notes MILAB; OR; 600.046; 605.203 Approved no
Call Number Admin @ si @ DSM2012 Serial 2151
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Author Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez
Title (up) Adaptation of a computer programming course to the EXHE requirements: evaluation five years later Type Miscellaneous
Year 2012 Publication European Journal of Engineering Education Abbreviated Journal
Volume 37 Issue 3 Pages 243-254
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Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes DAG; CIC; OR; invisible;MV Approved no
Call Number Admin @ si @ VBL2012 Serial 2070
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Author Monica Piñol
Title (up) Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning Type Report
Year 2010 Publication CVC Technical Report Abbreviated Journal
Volume 162 Issue Pages
Keywords
Abstract
Address Bellaterra (Barcelona)
Corporate Author Computer Vision Center Thesis Master's thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ Piñ2010 Serial 1936
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Author Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa
Title (up) Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers Type Conference Article
Year 2013 Publication CVPR Workshop on Ground Truth – What is a good dataset? Abbreviated Journal
Volume Issue Pages 688 - 693
Keywords Pedestrian Detection; Domain Adaptation
Abstract Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%.
Address Portland; oregon; June 2013
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CVPRW
Notes ADAS; 600.054; 600.057; 601.217 Approved yes
Call Number XVR2013; ADAS @ adas @ xvr2013a Serial 2220
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Author Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers
Title (up) Adapting Pedestrian Detection from Synthetic to Far Infrared Images Type Conference Article
Year 2013 Publication ICCV Workshop on Visual Domain Adaptation and Dataset Bias Abbreviated Journal
Volume Issue Pages
Keywords Domain Adaptation; Far Infrared; Pedestrian Detection
Abstract We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes.
Address Sydney; Australia; December 2013
Corporate Author Thesis
Publisher Place of Publication Sydney, Australy Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICCVW-VisDA
Notes ADAS; 600.054; 600.055; 600.057; 601.217;ISE Approved no
Call Number ADAS @ adas @ SRV2013 Serial 2334
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Author M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer
Title (up) Adaptive color attributes for real-time visual tracking Type Conference Article
Year 2014 Publication 27th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 1090 - 1097
Keywords
Abstract Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally
efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power.
This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional
variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms
state-of-the-art tracking methods while running at more than 100 frames per second.
Address Nottingham; UK; September 2014
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference CVPR
Notes CIC; LAMP; 600.074; 600.079 Approved no
Call Number Admin @ si @ DKF2014 Serial 2509
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Author V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich
Title (up) Adaptive Correlation Filters for Pattern Recognition Type Journal
Year 2006 Publication Pattern Recognition and Image Analysis Abbreviated Journal
Volume 16 Issue 3 Pages 425-431
Keywords Pattern recognition, Correlation filters, A adaptive filters
Abstract Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance.
Address
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Notes ISE Approved no
Call Number ISE @ ise @ KMA2006a Serial 673
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Author Monica Piñol; Angel Sappa; Ricardo Toledo
Title (up) Adaptive Feature Descriptor Selection based on a Multi-Table Reinforcement Learning Strategy Type Journal Article
Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM
Volume 150 Issue A Pages 106–115
Keywords Reinforcement learning; Q-learning; Bag of features; Descriptors
Abstract This paper presents and evaluates a framework to improve the performance of visual object classification methods, which are based on the usage of image feature descriptors as inputs. The goal of the proposed framework is to learn the best descriptor for each image in a given database. This goal is reached by means of a reinforcement learning process using the minimum information. The visual classification system used to demonstrate the proposed framework is based on a bag of features scheme, and the reinforcement learning technique is implemented through the Q-learning approach. The behavior of the reinforcement learning with different state definitions is evaluated. Additionally, a method that combines all these states is formulated in order to select the optimal state. Finally, the chosen actions are obtained from the best set of image descriptors in the literature: PHOW, SIFT, C-SIFT, SURF and Spin. Experimental results using two public databases (ETH and COIL) are provided showing both the validity of the proposed approach and comparisons with state of the art. In all the cases the best results are obtained with the proposed approach.
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Notes ADAS; 600.055; 600.076 Approved no
Call Number Admin @ si @ PST2015 Serial 2473
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Author David Geronimo; Angel Sappa; Antonio Lopez; Daniel Ponsa
Title (up) Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection Type Conference Article
Year 2007 Publication Proceedings of the 5th International Conference on Computer Vision Systems Abbreviated Journal ICVS
Volume Issue Pages
Keywords Pedestrian Detection
Abstract On–board pedestrian detection is in the frontier of the state–of–the–art since it implies processing outdoor scenarios from a mobile platform and searching for aspect–changing objects in cluttered urban environments. Most promising approaches include the development of classifiers based on feature selection and machine learning. However, they use a large number of features which compromises real–time. Thus, methods for running the classifiers in only a few image windows must be provided. In this paper we contribute in both aspects, proposing a camera
pose estimation method for adaptive sparse image sampling, as well as a classifier for pedestrian detection based on Haar wavelets and edge orientation histograms as features and AdaBoost as learning machine. Both proposals are compared with relevant approaches in the literature, showing comparable results but reducing processing time by four for the sampling tasks and by ten for the classification one.
Address Bielefeld (Germany)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
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Notes ADAS Approved no
Call Number ADAS @ adas @ gsl2007a Serial 786
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Author J.R. Serra; J.B. Subirana
Title (up) Adaptive non-cartesian networks for vision. Type Miscellaneous
Year 1997 Publication IX International Conference on Image Analysis and Processing. Abbreviated Journal
Volume Issue Pages
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Abstract
Address Florence
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
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Notes Approved no
Call Number Admin @ si @ SeS1997 Serial 212
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Author Miguel Reyes; Jose Ramirez Moreno; Juan R Revilla; Petia Radeva; Sergio Escalera
Title (up) ADiBAS: Sistema Multisensor de Adquisicion Automatica de Datos Corporales Objetivos, Robustos y Fiables para el Analisis de la Postura y el Movimiento Type Conference Article
Year 2011 Publication 6th Congreso Iberoamericano de Tecnologia de Apoyo a la Discapacidad Abbreviated Journal
Volume Issue Pages 939-944
Keywords
Abstract El análisis de la postura y del rango de movimiento son fundamentales para conocer la optimización del gesto y mejorar, de este modo, el rendimiento y la detección de posibles lesiones. Esta cuantificación es especialmente interesante en deportistas o en pacientes que presentan alguna lesión neurológica o del sistema musculo-esquelético, ya que permite conocer el proceso evolutivo de estos pacientes, evaluar la eficacia de la terapia aplicada y proponer, en caso necesario, una modificación del protocolo de tratamiento.
En este trabajo presentamos un sistema automático que permite, mediante una tecnología no invasiva, la captación automática de marcadores LED situados sobre el paciente y su posterior análisis con el fin de mostrar al especialista datos objetivos que permitan un mejor soporte diagnóstico. También se describe un
sistema analítico de la postura corporal sin marcadores, donde su ejecución durante secuencias dinámicas aporta un alto grado de naturalidad al paciente a la hora de realizar los ejercicios funcionales.
Address Palma de Mallorca
Corporate Author Thesis
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference IBERDISCAP
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ RRR2011 Serial 1768
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Author Maya Dimitrova; Petia Radeva; David Rotger; D. Boyadjiev; Juan J. Villanueva
Title (up) Advanced Cardiological Diagnosis via Intelligent Image Analysis Type Miscellaneous
Year 2004 Publication Abbreviated Journal
Volume Issue Pages
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Abstract
Address Varna (Bulgaria)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ DRR2004 Serial 477
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Author David Rotger; Cristina Cañero; Petia Radeva; J. Mauri; E. Fernandez; A. Tovar; V. Valle
Title (up) Advanced Visualization of 3D data of Intravascular Ultrasound Images. Type Miscellaneous
Year 2001 Publication Medical Data Analysis, Second International Symposium, ISMDA 2001, 245–250. Abbreviated Journal
Volume Issue Pages
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Address
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ RCR2001b Serial 157
Permanent link to this record
 
 
Author Debora Gil; Antoni Rosell
Title (up) Advances in Artificial Intelligence – How Lung Cancer CT Screening Will Progress? Type Abstract
Year 2019 Publication World Lung Cancer Conference Abbreviated Journal
Volume Issue Pages
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Abstract Invited speaker
Address Barcelona; September 2019
Corporate Author Thesis
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Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference IASLC WCLC
Notes IAM; 600.139; 600.145 Approved no
Call Number Admin @ si @ GiR2019 Serial 3361
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Author Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li
Title (up) Advances in Face Presentation Attack Detection Type Book Whole
Year 2023 Publication Advances in Face Presentation Attack Detection Abbreviated Journal
Volume Issue Pages
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Address
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Notes HUPBA Approved no
Call Number Admin @ si @ WGE2023a Serial 3955
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