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Author Antonio Lopez; Felipe Lumbreras; A. Martinez; Joan Serrat; Xavier Roca; X. Varona; Jordi Vitria
Title (up) Aplicaciones de la vision por computador a la industria. Type Miscellaneous
Year 1997 Publication CVC Abbreviated Journal
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Address
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Publisher Place of Publication Editor
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Notes ADAS;OR;ISE;MV Approved no
Call Number ADAS @ adas @ LLM1997b Serial 50
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Author Eirikur Agustsson; Radu Timofte; Sergio Escalera; Xavier Baro; Isabelle Guyon; Rasmus Rothe
Title (up) Apparent and real age estimation in still images with deep residual regressors on APPA-REAL database Type Conference Article
Year 2017 Publication 12th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract After decades of research, the real (biological) age estimation from a single face image reached maturity thanks to the availability of large public face databases and impressive accuracies achieved by recently proposed methods.
The estimation of “apparent age” is a related task concerning the age perceived by human observers. Significant advances have been also made in this new research direction with the recent Looking At People challenges. In this paper we make several contributions to age estimation research. (i) We introduce APPA-REAL, a large face image database with both real and apparent age annotations. (ii) We study the relationship between real and apparent age. (iii) We develop a residual age regression method to further improve the performance. (iv) We show that real age estimation can be successfully tackled as an apparent age estimation followed by an apparent to real age residual regression. (v) We graphically reveal the facial regions on which the CNN focuses in order to perform apparent and real age estimation tasks.
Address Washington;USA; May 2017
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FG
Notes HUPBA; no menciona Approved no
Call Number Admin @ si @ ATE2017 Serial 3013
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Author X. Varona; Jordi Gonzalez; Xavier Roca; Juan J. Villanueva
Title (up) Appearance Tracking for Video Surveillance Type Miscellaneous
Year 2003 Publication Abbreviated Journal
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Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ VGR2003a Serial 358
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Author J. Varona; Jordi Gonzalez; Xavier Roca; Juan J. Villanueva
Title (up) Appearance Tracking for Video Surveillance Type Miscellaneous
Year 2003 Publication In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science 2652:1041–1048 Abbreviated Journal
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Address Springer-Verlag
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 ISE Approved no
Call Number ISE @ ise @ VGR2003b Serial 425
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Author Fadi Dornaika; Angel Sappa
Title (up) Appearance-based 3D Face Tracker: An Evaluation Study Type Miscellaneous
Year 2005 Publication 2nd IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 121–128 Abbreviated Journal
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Address Beijing (China)
Corporate Author Thesis
Publisher Place of Publication Editor
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Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ DoS2005b Serial 580
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Author Bogdan Raducanu; Fadi Dornaika
Title (up) Appearance-based Face Recognition Using A Supervised Manifold Learning Framework Type Conference Article
Year 2012 Publication IEEE Workshop on the Applications of Computer Vision Abbreviated Journal
Volume Issue Pages 465-470
Keywords
Abstract Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance.
Address Breckenridge; CO; USA
Corporate Author Thesis
Publisher IEEE Xplore Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1550-5790 ISBN 978-1-4673-0233-3 Medium
Area Expedition Conference WACV
Notes OR;MV Approved no
Call Number Admin @ si @ RaD2012d Serial 1890
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Author Ernest Valveny; Enric Marti
Title (up) Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal
Volume Issue Pages
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Abstract We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.
Address
Corporate Author Thesis
Publisher Place of Publication Bangalore (India) 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 DAG;IAM; Approved no
Call Number IAM @ iam @ VAM1999a Serial 1657
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Author Ernest Valveny; Miquel Ferrer
Title (up) Application of Graph Embedding to Solve Graph Matchin Problems Type Conference Article
Year 2008 Publication Colloque International Francophone sur l’Ecrit et le Document Abbreviated Journal
Volume Issue Pages 13–18
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Abstract
Address Rouen (France)
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 CIFED’08
Notes DAG Approved no
Call Number DAG @ dag @ VaF2008 Serial 1063
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Author Gisel Bastidas-Guacho; Patricio Moreno; Boris X. Vintimilla; Angel Sappa
Title (up) Application on the Loop of Multimodal Image Fusion: Trends on Deep-Learning Based Approaches Type Conference Article
Year 2023 Publication 13th International Conference on Pattern Recognition Systems Abbreviated Journal
Volume 14234 Issue Pages 25–36
Keywords
Abstract Multimodal image fusion allows the combination of information from different modalities, which is useful for tasks such as object detection, edge detection, and tracking, to name a few. Using the fused representation for applications results in better task performance. There are several image fusion approaches, which have been summarized in surveys. However, the existing surveys focus on image fusion approaches where the application on the loop of multimodal image fusion is not considered. On the contrary, this study summarizes deep learning-based multimodal image fusion for computer vision (e.g., object detection) and image processing applications (e.g., semantic segmentation), that is, approaches where the application module leverages the multimodal fusion process to enhance the final result. Firstly, we introduce image fusion and the existing general frameworks for image fusion tasks such as multifocus, multiexposure and multimodal. Then, we describe the multimodal image fusion approaches. Next, we review the state-of-the-art deep learning multimodal image fusion approaches for vision applications. Finally, we conclude our survey with the trends of task-driven multimodal image fusion.
Address Guayaquil; Ecuador; July 2023
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 ICPRS
Notes MSIAU Approved no
Call Number Admin @ si @ BMV2023 Serial 3932
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Author M.J. Yzuel; J. Pladellorens; Joan Serrat; A. Dupuy
Title (up) Application restauration and edge detection techniques in the calculation of left ventricular volumes. Type Conference Article
Year 1993 Publication Optics in Medicine, Biology and Environmental Research : Selected contributions to the first International Conference on Optics within Life Sciences (OWLS I) Abbreviated Journal
Volume Issue Pages 374-375
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Abstract
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Notes ADAS Approved no
Call Number ADAS @ adas @ YPS1993 Serial 244
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Author Aura Hernandez-Sabate; Debora Gil;Eduard Fernandez-Nofrerias;Petia Radeva; Enric Marti
Title (up) Approaching Artery Rigid Dynamics in IVUS Type Journal Article
Year 2009 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI
Volume 28 Issue 11 Pages 1670-1680
Keywords Fourier analysis; intravascular ultrasound (IVUS) dynamics; longitudinal motion; quality measures; tissue deformation.
Abstract Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical 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 0278-0062 ISBN Medium
Area Expedition Conference
Notes IAM; MILAB Approved no
Call Number IAM @ iam @ HGF2009 Serial 1545
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Author Pierluigi Casale; Oriol Pujol; Petia Radeva
Title (up) Approximate Convex Hulls Family for One-Class Cassification Type Conference Article
Year 2011 Publication 10th International Workshop on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 106-115
Keywords
Abstract In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification.
Address Napoli, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium
Area Expedition Conference MCS
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ CPR2011b Serial 1761
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Author Pierluigi Casale
Title (up) Approximate Ensemble Methods for Physical Activity Recognition Applications Type Book Whole
Year 2011 Publication PhD Thesis, Universitat de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
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Abstract The main interest of this thesis focuses on computational methodologies able to
reduce the degree of complexity of learning algorithms and its application to physical
activity recognition.
Random Projections will be used to reduce the computational complexity in Multiple Classifier Systems. A new boosting algorithm and a new one-class classification
methodology have been developed. In both cases, random projections are used for
reducing the dimensionality of the problem and for generating diversity, exploiting in
this way the benefits that ensembles of classifiers provide in terms of performances
and stability. Moreover, the new one-class classification methodology, based on an ensemble strategy able to approximate a multidimensional convex-hull, has been proved
to over-perform state-of-the-art one-class classification methodologies.
The practical focus of the thesis is towards Physical Activity Recognition. A new
hardware platform for wearable computing application has been developed and used
for collecting data of activities of daily living allowing to study the optimal features
set able to successful classify activities.
Based on the classification methodologies developed and the study conducted on
physical activity classification, a machine learning architecture capable to provide a
continuous authentication mechanism for mobile-devices users has been worked out,
as last part of the thesis. The system, based on a personalized classifier, states on
the analysis of the characteristic gait patterns typical of each individual ensuring an
unobtrusive and continuous authentication mechanism
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Oriol Pujol;Petia Radeva
Language Summary Language Original Title
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ISSN ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ Cas2011 Serial 1837
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Author Pierluigi Casale; Oriol Pujol; Petia Radeva
Title (up) Approximate polytope ensemble for one-class classification Type Journal Article
Year 2014 Publication Pattern Recognition Abbreviated Journal PR
Volume 47 Issue 2 Pages 854-864
Keywords One-class classification; Convex hull; High-dimensionality; Random projections; Ensemble learning
Abstract In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets.
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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ISSN ISBN Medium
Area Expedition Conference
Notes MILAB; 605.203 Approved no
Call Number Admin @ si @ CPR2014a Serial 2469
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Author Bogdan Raducanu; Jordi Vitria
Title (up) Aprendiendo a Aprender: de Maquinas Listas a Maquinas Inteligentes Type Miscellaneous
Year 2006 Publication Campus Multidisciplinario en Percepcion e Inteligencia (Antionio Fernandez–Caballero et al., eds.), 1: 34–45 Abbreviated Journal
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Address Albacete (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
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Area Expedition Conference
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ RaV2006b Serial 714
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