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Author
M. Bressan; Jordi Vitria
Title
Nonparametric Discriminant Analysis and Nearest Neighbor Classification
Type
Journal Article
Year
2003
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
24
Issue
15
Pages
2743–2749
Keywords
Abstract
IF: 0.809
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
ISBN
Medium
Area
Expedition
Conference
Notes
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ BrV2003b
Serial
367
Permanent link to this record
Author
David Guillamet; Jordi Vitria
Title
Evaluation of distance metrics for recognition based on non-negative matrix factorization
Type
Journal Article
Year
2003
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
24
Issue
9-10
Pages
1599 –1605
Keywords
Abstract
IF: 0.809
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
ISBN
Medium
Area
Expedition
Conference
Notes
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ GuV2003b
Serial
380
Permanent link to this record
Author
David Guillamet; Jordi Vitria; B. Shiele
Title
Introducing a weighted non-negative matrix factorization for image classification
Type
Journal Article
Year
2003
Publication
Pattern Recognition Letters
Abbreviated Journal
PRL
Volume
24
Issue
14
Pages
2447–2454
Keywords
Abstract
IF: 0.809
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
ISBN
Medium
Area
Expedition
Conference
Notes
OR;MV
Approved
no
Call Number
BCNPCL @ bcnpcl @ GVS2003
Serial
382
Permanent link to this record
Author
Bogdan Raducanu; Fadi Dornaika
Title
A Supervised Non-linear Dimensionality Reduction Approach for Manifold Learning
Type
Journal Article
Year
2012
Publication
Pattern Recognition
Abbreviated Journal
PR
Volume
45
Issue
6
Pages
2432-2444
Keywords
Abstract
IF= 2.61
IF=2.61 (2010)
In this paper we introduce a novel supervised manifold learning technique called Supervised Laplacian Eigenmaps (S-LE), which makes use of class label information to guide the procedure of non-linear dimensionality reduction by adopting the large margin concept. The graph Laplacian is split into two components: within-class graph and between-class graph to better characterize the discriminant property of the data. Our approach has two important characteristics: (i) it adaptively estimates the local neighborhood surrounding each sample based on data density and similarity and (ii) the objective function simultaneously maximizes the local margin between heterogeneous samples and pushes the homogeneous samples closer to each other.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques, demonstrating its superiority. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variations in their appearance (such as hand or body pose, for instance.
Address
Corporate Author
Thesis
Publisher
Elsevier
Place of Publication
Editor
Language
Summary Language
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
0031-3203
ISBN
Medium
Area
Expedition
Conference
Notes
OR; MV
Approved
no
Call Number
Admin @ si @ RaD2012a
Serial
1884
Permanent link to this record
Author
Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu
Title
Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction
Type
Journal Article
Year
2012
Publication
Sensors
Abbreviated Journal
SENS
Volume
12
Issue
2
Pages
1702-1719
Keywords
Abstract
IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
Address
Corporate Author
Thesis
Publisher
Molecular Diversity Preservation International
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
MILAB; OR;HuPBA;MV
Approved
no
Call Number
Admin @ si @ EBV2012
Serial
1885
Permanent link to this record
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