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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
Natural Facial Expression Recognition Using Dynamic and Static Schemes |
Type |
Conference Article |
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Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
Abbreviated Journal |
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Volume |
5875 |
Issue |
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Pages |
730–739 |
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Abstract |
Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. |
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Las Vegas, USA |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-10330-8 |
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ISVC |
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Notes |
OR;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ RaD2009 |
Serial |
1257 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
A Novel Approach to Geometric Fitting of Implicit Quadrics |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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Volume |
5807 |
Issue |
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Pages |
121–132 |
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Abstract |
This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. |
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Address |
Bordeaux, France |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-04696-4 |
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ACIVS |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ RoS2009 |
Serial |
1194 |
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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
Type |
Conference Article |
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Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
Abbreviated Journal |
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Volume |
5815 |
Issue |
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Pages |
204–214 |
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Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
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Address |
Belgica |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-04666-7 |
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ICVS |
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ADAS |
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no |
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Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
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Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
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Title |
ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences |
Type |
Conference Article |
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Year |
2009 |
Publication |
12th International Conference on Medical Image and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
5762 |
Issue |
II |
Pages |
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Abstract |
The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers. |
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Address |
London, UK |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-04270-6 |
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Conference |
MICCAI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ CPF2009 |
Serial |
1228 |
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Permanent link to this record |
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Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva |
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Title |
Multi-class Binary Symbol Classification with Circular Blurred Shape Models |
Type |
Conference Article |
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Year |
2009 |
Publication |
15th International Conference on Image Analysis and Processing |
Abbreviated Journal |
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Volume |
5716 |
Issue |
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Pages |
1005–1014 |
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Keywords |
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Abstract |
Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements. |
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Address |
Salerno, Italy |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-04145-7 |
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Expedition |
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Conference |
ICIAP |
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Notes |
MILAB;HuPBA;DAG |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ EFP2009c |
Serial |
1186 |
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Permanent link to this record |
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Author |
L.Tarazon; D. Perez; N. Serrano; V. Alabau; Oriol Ramos Terrades; A. Sanchis; A. Juan |
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Title |
Confidence Measures for Error Correction in Interactive Transcription of Handwritten Text |
Type |
Conference Article |
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Year |
2009 |
Publication |
15th International Conference on Image Analysis and Processing |
Abbreviated Journal |
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Volume |
5716 |
Issue |
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Pages |
567-574 |
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Keywords |
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Abstract |
An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence. |
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Address |
Vietri sul Mare, Italy |
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Corporate Author |
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Publisher |
Springer Berlin Heidelberg |
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Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-04145-7 |
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Expedition |
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Conference |
ICIAP |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ TPS2009 |
Serial |
1871 |
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Permanent link to this record |
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Author |
Mehdi Mirza-Mohammadi; Sergio Escalera; Petia Radeva |
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Title |
Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization |
Type |
Conference Article |
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Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
5702 |
Issue |
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Pages |
748–756 |
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Keywords |
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Abstract |
Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the object categorization problem, an image is represented by an unsorted set of discrete visual words (BOVW). In these models, relations among visual words are performed after dictionary construction. However, close object regions can have far descriptions in the feature space, being grouped as different visual words. In this paper, we present a method for considering geometrical information of visual words in the dictionary construction step. Object interest regions are obtained by means of the Harris-Affine detector and then described using the SIFT descriptor. Afterward, a contextual-space and a feature-space are defined, and a merging process is used to fuse feature words based on their proximity in the contextual-space. Moreover, we use the Error Correcting Output Codes framework to learn the new dictionary in order to perform multi-class classification. Results show significant classification improvements when spatial information is taken into account in the dictionary construction step. |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-03766-5 |
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Conference |
CAIP |
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Notes |
HuPBA; MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ MEP2009 |
Serial |
1185 |
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Permanent link to this record |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa; I. Bardaji; Horst Bunke |
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Title |
Graph-based k-means clustering: A comparison of the set versus the generalized median graph |
Type |
Conference Article |
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Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
5702 |
Issue |
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Pages |
342–350 |
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Keywords |
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Abstract |
In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph. |
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Address |
Münster, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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Abbreviated Series Title |
LNCS |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-03766-5 |
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CAIP |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ FVS2009d |
Serial |
1219 |
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Permanent link to this record |
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Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-Preserving Smoothing of Biomedical Images |
Type |
Conference Article |
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Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
5702 |
Issue |
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Pages |
427-434 |
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Keywords |
non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. |
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Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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Address |
Münster, Germany |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Series Editor |
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Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-03766-5 |
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CAIP |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ GHB2009 |
Serial |
1527 |
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Permanent link to this record |
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Author |
Maria Salamo; Sergio Escalera; Petia Radeva |
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Title |
Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Conference on Case-Based Reasoning |
Abbreviated Journal |
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Volume |
5650 |
Issue |
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Pages |
298–312 |
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Keywords |
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Abstract |
Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches. |
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Address |
Seattle, USA |
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Corporate Author |
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Publisher |
Springer Berlin Heidelberg |
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Abbreviated Series Title |
LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-02998-1 |
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Conference |
ICCBR |
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Notes |
HuPBA; MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ SER2009 |
Serial |
1187 |
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Permanent link to this record |
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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Recoding Error-Correcting Output Codes |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
5519 |
Issue |
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Pages |
11–21 |
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Keywords |
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Abstract |
One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design. |
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Address |
Reykjavik (Iceland) |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-02325-5 |
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MCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ EPR2009d |
Serial |
1190 |
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Permanent link to this record |
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Author |
Oriol Pujol; Eloi Puertas; Carlo Gatta |
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Title |
Multi-scale Stacked Sequential Learning |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
5519 |
Issue |
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Pages |
262–271 |
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Keywords |
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Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
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Reykjavik, Iceland |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02325-5 |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PPG2009 |
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1260 |
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Author |
Carlo Gatta; Juan Diego Gomez; Francesco Ciompi; O. Rodriguez-Leor; Petia Radeva |
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Title |
Toward robust myocardial blush grade estimation in contrast angiography |
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Conference Article |
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Year |
2009 |
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4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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249–256 |
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The assessment of Myocardial Blush Grade after primary angioplasty is a precious diagnostic tool to understand if the patient needs further medication or the use of specifics drugs. Unfortunately, the assessment of MBG is difficult for non highly specialized staff. Experimental data show that there is poor correlation between MBG assessment of low and high specialized staff, thus reducing its applicability. This paper proposes a method able to achieve an objective measure of MBG, or a set of parameters that correlates with the MBG. The method tracks the blush area starting from just one single frame tagged by the physician. As a consequence, the blush area is kept isolated from contaminating phenomena such as diaphragm and arteries movements. We also present a method to extract four parameters that are expected to correlate with the MBG. Preliminary results show that the method is capable of extracting interesting information regarding the behavior of the myocardial perfusion. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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MILAB |
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BCNPCL @ bcnpcl @ GGC2009 |
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1161 |
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Author |
Francesco Ciompi; Oriol Pujol; O. Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva |
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Title |
Enhancing In-Vitro IVUS Data for Tissue Characterization |
Type |
Conference Article |
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2009 |
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4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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241–248 |
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Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ CPR2009a |
Serial |
1162 |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa |
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Title |
Median Graph Computation by means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subraph |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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346–353 |
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Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present a new genetic algorithm for the median graph computation. A set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity, show that we obtain good approximations of the median graph. Finally, we use the median graph in a real nearest neighbour classification showing that it leaves the box of the only-theoretical concepts and demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
ISBN ![sorted by ISBN field, descending order (down)](img/sort_desc.gif) |
978-3-642-02171-8 |
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IbPRIA |
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DAG |
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no |
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Call Number |
DAG @ dag @ FVS2009c |
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1174 |
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