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Author Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title Reactive object tracking with a single PTZ camera Type Conference Article
  Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1690–1693  
  Keywords  
  Abstract In this paper we describe a novel approach to reactive tracking of moving targets with a pan-tilt-zoom camera. The approach uses an extended Kalman filter to jointly track the object position in the real world, its velocity in 3D and the camera intrinsics, in addition to the rate of change of these parameters. The filter outputs are used as inputs to PID controllers which continuously adjust the camera motion in order to reactively track the object at a constant image velocity while simultaneously maintaining a desirable target scale in the image plane. We provide experimental results on simulated and real tracking sequences to show how our tracker is able to accurately estimate both 3D object position and camera intrinsics with very high precision over a wide range of focal lengths.  
  Address Istanbul (Turkey)  
  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 1051-4651 ISBN 978-1-4244-7542-1 Medium  
  Area Expedition Conference ICPR  
  Notes (up) ISE Approved no  
  Call Number DAG @ dag @ ABG2010 Serial 1418  
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Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva edit  doi
isbn  openurl
  Title Recursive Coarse-to-Fine Localization for fast Object Recognition Type Conference Article
  Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal  
  Volume 6313 Issue II Pages 280–293  
  Keywords  
  Abstract Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter.  
  Address Crete (Greece)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-15566-6 Medium  
  Area Expedition Conference ECCV  
  Notes (up) ISE Approved no  
  Call Number DAG @ dag @ PGB2010 Serial 1438  
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Author Carles Fernandez; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title Automatic Learning of Background Semantics in Generic Surveilled Scenes Type Conference Article
  Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal  
  Volume 6313 Issue II Pages 678–692  
  Keywords  
  Abstract Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis.  
  Address Crete (Greece)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-15551-2 Medium  
  Area Expedition Conference ECCV  
  Notes (up) ISE Approved no  
  Call Number ISE @ ise @ FGR2010 Serial 1439  
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Author Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez edit   pdf
doi  openurl
  Title Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns Type Journal Article
  Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages 7  
  Keywords  
  Abstract Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications.
 
  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 1110-8657 ISBN Medium  
  Area Expedition Conference  
  Notes (up) ISE Approved no  
  Call Number ISE @ ise @ AMR2010 Serial 1463  
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Author Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich edit  doi
openurl 
  Title Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception Type Journal Article
  Year 2010 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
  Volume 27 Issue 3 Pages 613–621  
  Keywords  
  Abstract In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%.  
  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 (up) ISE;CIC Approved no  
  Call Number CAT @ cat @ VGL2010 Serial 1275  
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Author David Rotger; Petia Radeva; N. Bruining edit  doi
openurl 
  Title Automatic Detection of Bioabsorbable Coronary Stents in IVUS Images using a Cascade of Classifiers Type Journal Article
  Year 2010 Publication IEEE Transactions on Information Technology in Biomedicine Abbreviated Journal TITB  
  Volume 14 Issue 2 Pages 535 – 537  
  Keywords  
  Abstract Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the late restenosis. These stents made of poly-L-lactic acid cause a very subtle acoustic shadow (compared to the metallic ones) making difficult the automatic detection and measurements in images. In this paper, we propose a novel approach based on a cascade of GentleBoost classifiers to detect the stent struts using structural features to code the information of the different subregions of the struts. A stochastic gradient descent method is applied to optimize the overall performance of the detector. Validation results of struts detection are very encouraging with an average F-measure of 81%.  
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ RRB2010 Serial 1287  
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Author Simone Balocco; O. Basset; G. Courbebaisse; E. Boni; Alejandro F. Frangi; P. Tortoli; C. Cachard edit  doi
openurl 
  Title Estimation Of Viscoelastic Properties Of Vessel Walls Using a Computational Model and Doppler Ultrasound Type Journal Article
  Year 2010 Publication Physics in Medicine and Biology Abbreviated Journal PMB  
  Volume 55 Issue 12 Pages 3557–3575  
  Keywords  
  Abstract Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.  
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ BBC2010 Serial 1312  
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Author Simone Balocco; O. Camara; E. Vivas; T. Sola; L. Guimaraens; H. A. van Andel; C. B. Majoie; J. M. Pozo; B. H. Bijnens; Alejandro F. Frangi edit  url
openurl 
  Title Feasibility of Estimating Regional Mechanical Properties of Cerebral Aneurysms In Vivo Type Journal Article
  Year 2010 Publication Medical Physics Abbreviated Journal MEDPHYS  
  Volume 37 Issue 4 Pages 1689–1706  
  Keywords  
  Abstract PURPOSE:
In this article, the authors studied the feasibility of estimating regional mechanical properties in cerebral aneurysms, integrating information extracted from imaging and physiological data with generic computational models of the arterial wall behavior.
METHODS:
A data assimilation framework was developed to incorporate patient-specific geometries into a given biomechanical model, whereas wall motion estimates were obtained from applying registration techniques to a pair of simulated MR images and guided the mechanical parameter estimation. A simple incompressible linear and isotropic Hookean model coupled with computational fluid-dynamics was employed as a first approximation for computational purposes. Additionally, an automatic clustering technique was developed to reduce the number of parameters to assimilate at the optimization stage and it considerably accelerated the convergence of the simulations. Several in silico experiments were designed to assess the influence of aneurysm geometrical characteristics and the accuracy of wall motion estimates on the mechanical property estimates. Hence, the proposed methodology was applied to six real cerebral aneurysms and tested against a varying number of regions with different elasticity, different mesh discretization, imaging resolution, and registration configurations.
RESULTS:
Several in silico experiments were conducted to investigate the feasibility of the proposed workflow, results found suggesting that the estimation of the mechanical properties was mainly influenced by the image spatial resolution and the chosen registration configuration. According to the in silico experiments, the minimal spatial resolution needed to extract wall pulsation measurements with enough accuracy to guide the proposed data assimilation framework was of 0.1 mm.
CONCLUSIONS:
Current routine imaging modalities do not have such a high spatial resolution and therefore the proposed data assimilation framework cannot currently be used on in vivo data to reliably estimate regional properties in cerebral aneurysms. Besides, it was observed that the incorporation of fluid-structure interaction in a biomechanical model with linear and isotropic material properties did not have a substantial influence in the final results.
 
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ BCV2010 Serial 1313  
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Author Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; H. Tizon; Xavier Carrillo; J. Mauri; Petia Radeva edit  doi
openurl 
  Title Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound Type Journal Article
  Year 2010 Publication Journal of the American College of Cardiology Abbreviated Journal JACC  
  Volume 56 Issue 13s1 Pages B119  
  Keywords  
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SFC2010b Serial 1364  
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Author Jose Seabra; F. Javier Sanchez; Francesco Ciompi; Petia Radeva edit  url
doi  isbn
openurl 
  Title Ultrasonographic Plaque Characterization using a Rayleigh Mixture Model Type Conference Article
  Year 2010 Publication 7th IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages 1–4  
  Keywords  
  Abstract From Nano to Macro
A correct modelling of tissue morphology is determinant for the identification of vulnerable plaques. This paper aims at describing the plaque composition by means of a Rayleigh Mixture Model applied to ultrasonic data. The effectiveness of using a mixture of distributions is established through synthetic and real ultrasonic data samples. Furthermore, the proposed mixture model is used in a plaque classification problem in Intravascular Ultrasound (IVUS) images of coronary plaques. A classifier tested on a set of 67 in-vitro plaques, yields an overall accuracy of 86% and sensitivity of 92%, 94% and 82%, for fibrotic, calcified and lipidic tissues, respectively. These results strongly suggest that different plaques types can be distinguished by means of the coefficients and Rayleigh parameters of the mixture distribution.
 
  Address Rotterdam (Netherlands)  
  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 1945-7928 ISBN 978-1-4244-4125-9 Medium  
  Area Expedition Conference ISBI  
  Notes (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SSC2010 Serial 1366  
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Author Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; Xavier Carrillo; R. Hemetsberger; Petia Radeva; J. Mauri; A. Bayes edit  openurl
  Title Canvis de volum a la arteria radial despres de la administracio de dos tractaments vasodilatadors. Avaluacio mitjançant ecografia intravascular Type Conference Article
  Year 2010 Publication 22nd Congres Societat Catalana de Cardiologia, Abbreviated Journal  
  Volume Issue Pages 179  
  Keywords  
  Abstract  
  Address Barcelona (Spain)  
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SFC2010a Serial 1367  
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Author Oriol Rodriguez-Leor; R. Hemetsberger; Francesco Ciompi; E Fernandez-Nofrerias; Angel Serrano; M. Bernet; Petia Radeva; J. Mauri; A. Bayes edit  openurl
  Title Caracteritzacio automatica de la placa mitjançant analisis del espectre de radiofreqüencia en estudi de ecografia intracoronaria: resultat de la fusio de dades invivo i exvivo Type Conference Article
  Year 2010 Publication 22nd Congres Societat Catalana de Cardiologia, Abbreviated Journal  
  Volume Issue Pages 131  
  Keywords  
  Abstract  
  Address Barcelona (Spain)  
  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 (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ RHC2010 Serial 1368  
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Author Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; Oriol Rodriguez-Leor; Petia Radeva edit  openurl
  Title Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation Type Conference Article
  Year 2010 Publication 13th international conference on Medical image computing and computer-assisted intervention Abbreviated Journal  
  Volume II Issue Pages 59-67  
  Keywords  
  Abstract Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin 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 MICCAI  
  Notes (up) MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ GBC2010 Serial 1447  
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Author Carolina Malagelada; F.De Lorio; Fernando Azpiroz; Santiago Segui; Petia Radeva; Anna Accarino; J.Santos; Juan R. Malagelada edit  openurl
  Title Intestinal Dysmotility in Patients with Functional Intestinal Disorders Demonstrated by Computer Vision Analysis of Capsule Endoscopy Images Type Conference Article
  Year 2010 Publication 18th United European Gastroenterology Week Abbreviated Journal  
  Volume 56 Issue 3 Pages A19-20  
  Keywords  
  Abstract  
  Address Barcelona  
  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 UEGW  
  Notes (up) MILAB Approved no  
  Call Number Admin @ si @ MLA2010 Serial 1779  
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Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  openurl
  Title Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications Type Conference Article
  Year 2010 Publication European Conference on Machine Learning Abbreviated Journal  
  Volume I Issue Pages 119-128  
  Keywords  
  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 ECML  
  Notes (up) MILAB; OR;HUPBA;MV Approved no  
  Call Number Admin @ si @ BEB2010 Serial 1775  
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