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Author Jian Yang; Zhong Jin; Jing-Yu Yang; David Zhang; Alejandro F. Frangi edit  url
openurl 
  Title Essence of kernel Fisher discriminant: KPCA plus LDA Type Journal
  Year 2004 Publication Pattern Recognition, 37(10): 2097–2100 (IF: 2.176) Abbreviated Journal  
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  Notes Approved no  
  Call Number Admin @ si @ YJY2004 Serial 480  
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Author Yong Xu; Jing-Yu Yang; Zhong Jin edit  url
openurl 
  Title A novel method for Fisher discriminant analysis Type Journal
  Year 2004 Publication Pattern Recognition, 37(2):381–384 (IF: 2.176) Abbreviated Journal  
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  Notes Approved no  
  Call Number Admin @ si @ XYJ2004 Serial 481  
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Author Misael Rosales; Petia Radeva; J. Mauri; Oriol Pujol edit  url
openurl 
  Title Simulation Model of Intravascular Ultrasound Images Type Miscellaneous
  Year 2004 Publication MICCAI, 2004, Saint Melo, France Abbreviated Journal  
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  Address Springer Verlag  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ RRM2004b Serial 464  
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Author Georg Langs; Petia Radeva; David Rotger; Francesc Carreras edit  url
openurl 
  Title Building and Registering Parameterized 3D Models of Vessel Trees for Visualization during Intervention Type Miscellaneous
  Year 2004 Publication 17th International Conference on Pattern Recognition, ICPR’04 Abbreviated Journal  
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  Address Cambridge, United Kingdom  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ LRR2004b Serial 463  
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Author Sergio Escalera; Petia Radeva edit  url
openurl 
  Title Fast greyscale road sign model matching and recognition Type Miscellaneous
  Year 2004 Publication CCIA, IOS Press Abbreviated Journal  
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  Address Barcelona, Spain  
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  Notes HuPBA; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ EsR2004 Serial 469  
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Author Jaume Amores; N. Sebe; Petia Radeva; Theo Gevers; A. Smeulders edit  url
openurl 
  Title Boosting Contextual Information in Content-based Image Retrieval Type Miscellaneous
  Year 2004 Publication 6th ACM SIGMM International Workshop on Multimedia Information Retrieval Abbreviated Journal  
  Volume Issue Pages  
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  Address New York, USA  
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  Notes MILAB;ISE Approved no  
  Call Number ADAS @ adas @ ASR2004 Serial 466  
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Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
url  isbn
openurl 
  Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
  Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume 113 Issue Pages 77-84  
  Keywords Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision  
  Abstract Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.  
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  Publisher IOS Press Place of Publication Editor J. Vitrià, P. Radeva and I. Aguiló  
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  ISSN ISBN 978-1-58603-466-5 Medium  
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  Notes MV;IAM;MILAB;SIAI Approved no  
  Call Number IAM @ iam @ VGR2004 Serial 1663  
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Author Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Texture Segmentation by Statistical Deformable Models Type Journal
  Year 2004 Publication International Journal of Image and Graphics Abbreviated Journal IJIG  
  Volume 4 Issue 3 Pages 433-452  
  Keywords Texture segmentation, parametric active contours, statistic snakes  
  Abstract Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model.  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ PuR2004a Serial 505  
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Author Debora Gil; Petia Radeva edit   pdf
doi  openurl
  Title A Regularized Curvature Flow Designed for a Selective Shape Restoration Type Journal Article
  Year 2004 Publication IEEE Transactions on Image Processing Abbreviated Journal  
  Volume 13 Issue Pages 1444–1458  
  Keywords Geometric flows, nonlinear filtering, shape recovery.  
  Abstract Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization.  
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  Notes IAM;MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ GiR2004b Serial 491  
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias edit   pdf
doi  openurl
  Title Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images Type Conference Article
  Year 2004 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 31 Issue Pages 229-232  
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  Abstract The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles  
  Address  
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  Publisher Place of Publication Chicago (USA) Editor  
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  Notes IAM; MILAB Approved no  
  Call Number IAM @ iam @ HGR2004 Serial 1555  
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Author Debora Gil; Petia Radeva edit   pdf
doi  openurl
  Title Shape Restoration via a Regularized Curvature Flow Type Journal Article
  Year 2004 Publication Journal of Mathematical Imaging and Vision Abbreviated Journal  
  Volume 21 Issue 3 Pages 205-223  
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  Abstract Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.
In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications.		  
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  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GiR2004c Serial 1532  
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Author Jordi Gonzalez edit  openurl
  Title Human Sequence Evaluation: the Key-frame Approach Type Book Whole
  Year 2004 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Corporate Author Thesis Ph.D. thesis  
  Publisher Place of Publication Editor Xavier Roca;Javier Varona  
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  Notes Approved no  
  Call Number ISE @ ise @ Gon2004 Serial 362  
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Author Robert Benavente; Maria Vanrell edit  openurl
  Title Fuzzy Colour Naming Based on Sigmoid Membership Functions. Type Miscellaneous
  Year 2004 Publication CGIV 2004 Second European Conference on Colour in Graphics, Imaging and Vision, 135:139 Abbreviated Journal  
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  Address Aachen (Germany)  
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  Notes CIC Approved no  
  Call Number CAT @ cat @ BeV2004 Serial 441  
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Author M. Bressan; David Guillamet; Jordi Vitria edit  openurl
  Title Multiclass Object Recognition using Class-Conditional Independent Component Analisis Type Journal
  Year 2004 Publication Cybernetics and Systems, 35/1:35–61 (IF: 0.768) Abbreviated Journal  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BGV2004 Serial 442  
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Author David Guillamet edit  openurl
  Title Statistical Local Appearance Models for Object Recognition Type Book Whole
  Year 2004 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Abstract  
  Address Bellaterra  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Place of Publication Editor Jordi Vitria  
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  Notes Approved no  
  Call Number Admin @ si @ Gui2004 Serial 444  
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