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Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Decoding of Ternary Error Correcting Output Codes |
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2006 |
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11th Iberoamerican Congress on Pattern Recognition (CIARP´06), LNCS 4225: 753–763 |
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Cancun (Mexico) |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2006e |
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696 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
Face Verification using External Features |
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2006 |
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7th International Conference on Automatic Face and Gesture Recognition (FG´06), 132– 137 |
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Southampton (United Kingdom) |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ LMV2006a |
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707 |
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Author |
Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
On the Use of External Face Features for Identity Verification |
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2006 |
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Journal of Multimedia, 1(4): 11–20 |
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1 |
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4 |
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11-20 |
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Face Verification, Computer Vision, Machine Learning |
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In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded. |
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OR;MV |
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BCNPCL @ bcnpcl @ LMV2006b |
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708 |
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David Masip; Jordi Vitria |
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Title |
Boosted discriminant projections for nearest neighbor classification |
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2006 |
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Pattern Recognition, 39(2): 164–170 |
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OR;MV |
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BCNPCL @ bcnpcl @ MaV2006 |
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634 |
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Author |
Enric Marti; J. Rocarias; A. Sanchez; Petia Radeva; Ricardo Toledo; Jordi Vitria |
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Title |
Caronte: una propuesta de entorno de gestion documental para asignaturas de Ingenieria Informatica |
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Miscellaneous |
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2006 |
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IV Congreso Internacional Docencia Universitaria e Innovacion (CIDUI´06) |
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Barcelona |
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IAM;RV;OR;MILAB;ADAS;MV |
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no |
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BCNPCL @ bcnpcl @ MRS2006a |
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1122 |
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Enric Marti; J. Rocarias; A. Sanchez; Petia Radeva; Ricardo Toledo; Jordi Vitria |
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Title |
Caronte: un gestor documental para asignaturas del EEES |
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2006 |
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III Jornades de Innovacio Docent |
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UAB, Bellaterra |
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IAM;RV;OR;MILAB;ADAS;MV |
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BCNPCL @ bcnpcl @ MRS2006b |
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1124 |
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Author |
Xavier Otazu; Oriol Pujol |
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Title |
Wavelet based approach to cluster analysis. Application on low dimensional data sets |
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Journal Article |
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2006 |
Publication |
Pattern Recognition Letters |
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PRL |
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27 |
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14 |
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1590–1605 |
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MILAB; CIC; HuPBA |
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no |
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BCNPCL @ bcnpcl @ OtP2006 |
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658 |
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Author |
Oriol Pujol; Petia Radeva; Jordi Vitria |
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Title |
Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes |
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2006 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6): 1007–1012 |
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OR;MILAB;HuPBA;MV |
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no |
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BCNPCL @ bcnpcl @ PRV2006a |
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646 |
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Author |
F. Pla; Petia Radeva; Jordi Vitria |
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Title |
Pattern Recognition: Progress, Directions and Applications |
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2006 |
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84-933652-6-2 |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ PRV2006b |
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771 |
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Author |
Bogdan Raducanu; Jordi Vitria |
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Title |
Aprendiendo a Aprender: de Maquinas Listas a Maquinas Inteligentes |
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2006 |
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Campus Multidisciplinario en Percepcion e Inteligencia (Antionio Fernandez–Caballero et al., eds.), 1: 34–45 |
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Albacete (Spain) |
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OR;MV |
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BCNPCL @ bcnpcl @ RaV2006b |
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714 |
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Bogdan Raducanu; Jordi Vitria |
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Title |
A Robust Particle Filter-Based Face Tracker Using Combination of Color and Geometric Information |
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2006 |
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International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 922–933 |
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OR;MV |
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BCNPCL @ bcnpcl @ RaV2006c |
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715 |
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Author |
David Rotger; Petia Radeva; Oriol Rodriguez |
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Title |
Vessel Tortuosity Extraction from IVUS Images |
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Miscellaneous |
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2006 |
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Computers in Cardiology (CiC´06), 33: 689–692 |
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Valencia (Spain) |
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MILAB |
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BCNPCL @ bcnpcl @ RRR2006 |
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762 |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions |
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Book Chapter |
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2006 |
Publication |
9th International Conference on Medical Image Computing and Computer–Assisted Intervention |
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4191 |
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161–168 |
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Abstract |
Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions. |
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Copenhagen (Denmark) |
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Springer Verlag |
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Berlin Heidelberg |
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R. Larsen, M. Nielsen, and J. Sporring |
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800 |
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MICCAI06 |
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MV;OR;MILAB;SIAI |
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BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 |
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725 |
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Jordi Vitria; M. Bressan; Petia Radeva |
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Title |
Bayesian classification of cork stoppers using class-conditional independent component analysis |
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2006 |
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IEEE Transactions on Systems, Man and Cybernetics (Part C), 36(6) |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VBR2006 |
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723 |
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Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva |
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Title |
ROC curves and video analysis optimization in intestinal capsule endoscopy |
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2006 |
Publication |
Pattern Recognition Letters |
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PRL |
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27 |
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8 |
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875–881 |
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ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy |
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Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions. |
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800 |
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MILAB;MV;SIAI |
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BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 |
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647 |
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