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Author Sergio Escalera; Petia Radeva
Title (up) Fast greyscale road sign model matching and recognition Type Miscellaneous
Year 2004 Publication CCIA, IOS Press Abbreviated Journal
Volume Issue Pages
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Abstract
Address Barcelona, Spain
Corporate Author Thesis
Publisher Place of Publication Editor
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Area Expedition Conference
Notes HuPBA; MILAB Approved no
Call Number BCNPCL @ bcnpcl @ EsR2004 Serial 469
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Author Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate; Marçal Rusiñol; Francesc J. Ferri
Title (up) Fast Kernel Generalized Discriminative Common Vectors for Feature Extraction Type Journal Article
Year 2018 Publication Journal of Mathematical Imaging and Vision Abbreviated Journal JMIV
Volume 60 Issue 4 Pages 512-524
Keywords
Abstract This paper presents a supervised subspace learning method called Kernel Generalized Discriminative Common Vectors (KGDCV), as a novel extension of the known Discriminative Common Vectors method with Kernels. Our method combines the advantages of kernel methods to model complex data and solve nonlinear
problems with moderate computational complexity, with the better generalization properties of generalized approaches for large dimensional data. These attractive combination makes KGDCV specially suited for feature extraction and classification in computer vision, image processing and pattern recognition applications. Two different approaches to this generalization are proposed, a first one based on the kernel trick (KT) and a second one based on the nonlinear projection trick (NPT) for even higher efficiency. Both methodologies
have been validated on four different image datasets containing faces, objects and handwritten digits, and compared against well known non-linear state-of-art methods. Results show better discriminant properties than other generalized approaches both linear or kernel. In addition, the KGDCV-NPT approach presents a considerable computational gain, without compromising the accuracy of the model.
Address
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Notes DAG; ADAS; 600.086; 600.130; 600.121; 600.118; 600.129 Approved no
Call Number Admin @ si @ DMH2018a Serial 3062
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Author Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; J. M. Ferre; Petia Radeva
Title (up) Fast Rigid Registration of Vascular Structures in IVUS Sequences Type Journal Article
Year 2009 Publication IEEE Transactions on Information Technology in Biomedicine Abbreviated Journal
Volume 13 Issue 6 Pages 106-1011
Keywords
Abstract Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns 3.16 frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation.
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 1089-7771 ISBN Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ GPL2009 Serial 1250
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Author Jaume Amores; N. Sebe; Petia Radeva
Title (up) Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors Type Miscellaneous
Year 2005 Publication IEEE Computer Society, International Conference on Computer Vision and Pattern Recognition (CVPR’05), 2(2):769–774 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address San Diego, CA (USA)
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 ADAS @ adas @ ASR2005a Serial 541
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Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados
Title (up) Fast Structural Matching for Document Image Retrieval through Spatial Databases Type Conference Article
Year 2014 Publication Document Recognition and Retrieval XXI Abbreviated Journal
Volume 9021 Issue Pages
Keywords Document image retrieval; distance transform; MSER; spatial database
Abstract The structure of document images plays a signi cant role in document analysis thus considerable e orts have been made towards extracting and understanding document structure, usually in the form of layout analysis approaches. In this paper, we rst employ Distance Transform based MSER (DTMSER) to eciently extract stable document structural elements in terms of a dendrogram of key-regions. Then a fast structural matching method is proposed to query the structure of document (dendrogram) based on a spatial database which facilitates the formulation of advanced spatial queries. The experiments demonstrate a signi cant improvement in a document retrieval scenario when compared to the use of typical Bag of Words (BoW) and pyramidal BoW descriptors.
Address Amsterdam; 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 SPIE-DRR
Notes DAG; 600.056; 600.061; 600.077 Approved no
Call Number Admin @ si @ GRK2014a Serial 2496
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Author F. Lopez; J.M. Valiente; Ramon Baldrich; Maria Vanrell
Title (up) Fast surface grading using color statistics in the CIELab space Type Book Chapter
Year 2005 Publication LNCS 1: 666–673 Abbreviated Journal
Volume Issue Pages
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Address Germany
Corporate Author Thesis
Publisher Place of Publication Editor
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Notes CIC Approved no
Call Number CAT @ cat @ LVB2005 Serial 641
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Author Sergio Escalera
Title (up) Fast traffic model matching and recognition on gray-scale images Type Report
Year 2005 Publication CVC Technical Report #84 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address CVC (UAB)
Corporate Author Thesis
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Area Expedition Conference
Notes MILAB; HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ Esc2005 Serial 572
Permanent link to this record
 
 
Author Xavier Baro
Title (up) Fast traffic sign detection on gray-scale images Type Report
Year 2005 Publication CVC Technical Report #82 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address CVC (UAB)
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 OR;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ Bar2005 Serial 550
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Author Dena Bazazian; Raul Gomez; Anguelos Nicolaou; Lluis Gomez; Dimosthenis Karatzas; Andrew Bagdanov
Title (up) Fast: Facilitated and accurate scene text proposals through fcn guided pruning Type Journal Article
Year 2019 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 119 Issue Pages 112-120
Keywords
Abstract Class-specific text proposal algorithms can efficiently reduce the search space for possible text object locations in an image. In this paper we combine the Text Proposals algorithm with Fully Convolutional Networks to efficiently reduce the number of proposals while maintaining the same recall level and thus gaining a significant speed up. Our experiments demonstrate that such text proposal approaches yield significantly higher recall rates than state-of-the-art text localization techniques, while also producing better-quality localizations. Our results on the ICDAR 2015 Robust Reading Competition (Challenge 4) and the COCO-text datasets show that, when combined with strong word classifiers, this recall margin leads to state-of-the-art results in end-to-end scene text recognition.
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Notes DAG; 600.084; 600.121; 600.129 Approved no
Call Number Admin @ si @ BGN2019 Serial 3342
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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
Title (up) 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
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ BCV2010 Serial 1313
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez
Title (up) Feature Detectors and Feature Descriptors: Where We Are Now Type Report
Year 2010 Publication CVC Technical Report Abbreviated Journal
Volume 154 Issue Pages
Keywords
Abstract Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours.
Address
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Area 800 Expedition Conference
Notes MV;SIAI Approved no
Call Number Admin @ si @ BVS2010; IAM @ iam @ BVS2010 Serial 1348
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Author Katerine Diaz; Jesus Martinez del Rincon; Marçal Rusiñol; Aura Hernandez-Sabate
Title (up) Feature Extraction by Using Dual-Generalized Discriminative Common Vectors Type Journal Article
Year 2019 Publication Journal of Mathematical Imaging and Vision Abbreviated Journal JMIV
Volume 61 Issue 3 Pages 331-351
Keywords Online feature extraction; Generalized discriminative common vectors; Dual learning; Incremental learning; Decremental learning
Abstract In this paper, a dual online subspace-based learning method called dual-generalized discriminative common vectors (Dual-GDCV) is presented. The method extends incremental GDCV by exploiting simultaneously both the concepts of incremental and decremental learning for supervised feature extraction and classification. Our methodology is able to update the feature representation space without recalculating the full projection or accessing the previously processed training data. It allows both adding information and removing unnecessary data from a knowledge base in an efficient way, while retaining the previously acquired knowledge. The proposed method has been theoretically proved and empirically validated in six standard face recognition and classification datasets, under two scenarios: (1) removing and adding samples of existent classes, and (2) removing and adding new classes to a classification problem. Results show a considerable computational gain without compromising the accuracy of the model in comparison with both batch methodologies and other state-of-art adaptive methods.
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Notes DAG; ADAS; 600.084; 600.118; 600.121; 600.129 Approved no
Call Number Admin @ si @ DRR2019 Serial 3172
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Author David Masip; Jordi Vitria
Title (up) Feature Extraction for Nearest Neighbor Classification. Application to Gender Recognition Type Journal
Year 2005 Publication International Journal of Intelligent Systems, 20(5): 561–576 (IF: 0.657) Abbreviated Journal
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Address
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ MaV2005 Serial 562
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Author David Masip; M. Bressan; Jordi Vitria
Title (up) Feature extraction methods for real-time face detection and classification Type Journal
Year 2005 Publication Eurasip Journal on Applied Signal Processing, 13: 2061–2071 Abbreviated Journal
Volume Issue Pages
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Address
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ MBV2005 Serial 612
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Author P. Ricaurte ; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa
Title (up) Feature Point Descriptors: Infrared and Visible Spectra Type Journal Article
Year 2014 Publication Sensors Abbreviated Journal SENS
Volume 14 Issue 2 Pages 3690-3701
Keywords
Abstract This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
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Notes ADAS;600.055; 600.076 Approved no
Call Number Admin @ si @ RCA2014a Serial 2474
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