| Records |
| Author |
David Masip; Jordi Vitria |
| Title |
Boosted discriminant projections for nearest neighbor classification |
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Journal |
| Year |
2006 |
Publication |
Pattern Recognition, 39(2): 164–170 |
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OR;MV |
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no |
| Call Number |
BCNPCL @ bcnpcl @ MaV2006 |
Serial |
634 |
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| Author |
Agata Lapedriza; David Masip; Jordi Vitria |
| Title |
Face Verification using External Features |
Type |
Miscellaneous |
| Year |
2006 |
Publication |
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 |
Serial |
707 |
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| Author |
Agata Lapedriza; David Masip; Jordi Vitria |
| Title |
On the Use of External Face Features for Identity Verification |
Type |
Journal |
| Year |
2006 |
Publication |
Journal of Multimedia, 1(4): 11–20 |
Abbreviated Journal |
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| Volume |
1 |
Issue |
4 |
Pages |
11-20 |
| Keywords |
Face Verification, Computer Vision, Machine Learning |
| Abstract |
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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no |
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BCNPCL @ bcnpcl @ LMV2006b |
Serial |
708 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
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 |
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Albacete (Spain) |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2006b |
Serial |
714 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
A Robust Particle Filter-Based Face Tracker Using Combination of Color and Geometric Information |
Type |
Book Chapter |
| Year |
2006 |
Publication |
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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no |
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BCNPCL @ bcnpcl @ RaV2006c |
Serial |
715 |
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| Author |
Fadi Dornaika; Bogdan Raducanu |
| Title |
Recognizing Facial Expressions in Videos Using a Facial Action Analysis-Synthesis Scheme |
Type |
Miscellaneous |
| Year |
2006 |
Publication |
International Conference on Advanced Video and Signal Based Surveillance, (AVSS 2006), ISBN: 0–7695–2688–8 |
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Sydney (Australia) |
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| Notes |
OR;MV |
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no |
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BCNPCL @ bcnpcl @ DoR2006 |
Serial |
799 |
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| Author |
Jordi Vitria; M. Bressan; Petia Radeva |
| Title |
Bayesian classification of cork stoppers using class-conditional independent component analysis |
Type |
Journal |
| Year |
2006 |
Publication |
IEEE Transactions on Systems, Man and Cybernetics (Part C), 36(6) |
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| Notes |
OR;MILAB;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VBR2006 |
Serial |
723 |
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| Author |
F. Pla; Petia Radeva; Jordi Vitria |
| Title |
Pattern Recognition: Progress, Directions and Applications |
Type |
Book Whole |
| Year |
2006 |
Publication |
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ISBN |
84-933652-6-2 |
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| Notes |
OR;MILAB;MV |
Approved |
no |
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BCNPCL @ bcnpcl @ PRV2006b |
Serial |
771 |
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| Author |
Oriol Pujol; Petia Radeva; Jordi Vitria |
| Title |
Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes |
Type |
Journal |
| Year |
2006 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6): 1007–1012 |
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| Notes |
OR;MILAB;HuPBA;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ PRV2006a |
Serial |
646 |
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| Author |
Fernando Vilariño |
| Title |
A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy |
Type |
Book Whole |
| Year |
2006 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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| Abstract |
Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video.
In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way. |
| Address |
CVC (UAB) |
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Thesis |
Ph.D. thesis |
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Editor |
Petia Radeva |
| Language |
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Summary Language |
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Series Issue |
84-933652-7-0 |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ Vil2006; IAM @ iam @ Vil2006 |
Serial |
738 |
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| Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
| Title |
Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions |
Type |
Book Chapter |
| Year |
2006 |
Publication |
9th International Conference on Medical Image Computing and Computer–Assisted Intervention |
Abbreviated Journal |
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| Volume |
4191 |
Issue |
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Pages |
161–168 |
| Keywords |
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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. |
| Address |
Copenhagen (Denmark) |
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| Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
R. Larsen, M. Nielsen, and J. Sporring |
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LNCS |
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Edition |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
MICCAI06 |
| Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 |
Serial |
725 |
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| Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
| Title |
Cascade analysis for intestinal contraction detection |
Type |
Conference Article |
| Year |
2006 |
Publication |
20th International Congress and exhibition Computer Assisted Radiology and Surgery |
Abbreviated Journal |
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Issue |
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Pages |
9-10 |
| Keywords |
intestine video analysis, anisotropic features, support vector machine, cascade of classifiers |
| Abstract |
In this work, we address the study of intestinal contractions in a novel approach based on a machine learning framework to process data from Wireless Capsule Video Endoscopy. Wireless endoscopy represents a unique way to visualize the intestine motility by creating long videos to visualize intestine dynamics. In this paper we argue that to analyze huge amount of wireless endoscopy data and define robust methods for contraction detection we should base our approach on sophisticated machine learning techniques. In particular, we propose a cascade of classifiers in order to remove different physiological phenomenon and obtain the motility pattern of small intestines. Our results show obtaining high specificity and sensitivity rates that highlight the high efficiency of the selected approach and support the feasibility of the proposed methodology in the automatic detection and analysis of intestine contractions. |
| Address |
Osaka (Japan) |
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800 |
Expedition |
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Conference |
CARS |
| Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VSV2006a; IAM @ iam @ VSV2006h |
Serial |
726 |
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| Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
| Title |
Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy |
Type |
Conference Article |
| Year |
2006 |
Publication |
18th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
4 |
Issue |
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Pages |
719-722 |
| Keywords |
Clinical diagnosis , Endoscopes , Fluids and secretions , Gabor filters , Hospitals , Image sequence analysis , Intestines , Lighting , Shape , Visualization |
| Abstract |
Wireless capsule video endoscopy is a novel and challenging clinical technique, whose major reported drawback relates to the high amount of time needed for video visualization. In this paper, we propose a method for the rejection of the parts of the video resulting not valid for analysis by means of automatic detection of intestinal juices. We applied Gabor filters for the characterization of the bubble-like shape of intestinal juices in fasting patients. Our method achieves a significant reduction in visualization time, with no relevant loss of valid frames. The proposed approach is easily extensible to other image analysis scenarios where the described pattern of bubbles can be found. |
| Address |
Hong Kong |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
0-7695-2521-0 |
Medium |
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| Area |
800 |
Expedition |
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Conference |
ICPR |
| Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VSV2006b; IAM @ iam @ VSV2006g |
Serial |
727 |
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| Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
| Title |
Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions |
Type |
Book Chapter |
| Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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| Volume |
4225 |
Issue |
|
Pages |
178–187 |
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| Abstract |
This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. |
| Address |
Cancun (Mexico) |
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Thesis |
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| Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
.F. Mart ́ınez-Trinidad et al |
| Language |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
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ISBN |
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800 |
Expedition |
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| Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f |
Serial |
728 |
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| Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
| Title |
A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment |
Type |
Book Chapter |
| Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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| Volume |
4225 |
Issue |
|
Pages |
188–197 |
| Keywords |
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| Abstract |
Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment. |
| Address |
Cancun (Mexico) |
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Thesis |
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| Publisher |
Springer Verlag |
Place of Publication |
Berlin-Heidelberg |
Editor |
J.P. Martinez–Trinidad et al |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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| Area |
800 |
Expedition |
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Conference |
CIARP06 |
| Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e |
Serial |
729 |
| Permanent link to this record |
