| Records |
Author  |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Texture-independent recognition of facial expressions in image snapshots and videos |
Type |
Journal Article |
| Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
| Volume |
24 |
Issue |
4 |
Pages |
811-820 |
| Keywords |
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| Abstract |
This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. |
| Address |
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Thesis |
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| Publisher |
Springer-Verlag |
Place of Publication |
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| Language |
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Edition |
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| ISSN |
0932-8092 |
ISBN |
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Conference |
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| Notes |
OR; 600.046; 605.203;MV |
Approved |
no |
| Call Number |
Admin @ si @ RaD2013 |
Serial |
2230 |
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| Author |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Out-of-Sample Embedding by Sparse Representation |
Type |
Conference Article |
| Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
Abbreviated Journal |
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| Volume |
7626 |
Issue |
|
Pages |
336-344 |
| Keywords |
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| Abstract |
A critical aspect of non-linear dimensionality reduction techniques is represented by the construction of the adjacency graph. The difficulty resides in finding the optimal parameters, a process which, in general, is heuristically driven. Recently, sparse representation has been proposed as a non-parametric solution to overcome this problem. In this paper, we demonstrate that this approach not only serves for the graph construction, but also represents an efficient and accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. Experimental results conducted on some challenging datasets confirmed the robustness of our approach and its superiority when compared to existing techniques. |
| Address |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
Medium |
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| Area |
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Expedition |
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Conference |
SSPR&SPR |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RaD2012c |
Serial |
2175 |
| Permanent link to this record |
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| Author |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Pose-Invariant Face Recognition in Videos for Human-Machine Interaction |
Type |
Conference Article |
| Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
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| Volume |
7584 |
Issue |
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Pages |
566.575 |
| Keywords |
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| Abstract |
Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach. |
| Address |
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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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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-33867-0 |
Medium |
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| Area |
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Expedition |
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Conference |
ECCVW |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RaD2012e |
Serial |
2182 |
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| |
| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Real-Time Face Tracking for Context-Aware Computing |
Type |
Miscellaneous |
| Year |
2005 |
Publication |
8th Catalan Conference on Artificial Intelligence (CCIA 2005) (published in |
Abbreviated Journal |
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Issue |
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Pages |
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Place of Publication |
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Editor |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2005a |
Serial |
560 |
| Permanent link to this record |
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| |
| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Real-Time Face Tracking for Context-Aware Computing |
Type |
Book Chapter |
| Year |
2005 |
Publication |
Artificial Intelligence Research and Development, IOS Press, 91–98 |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Amsterdam |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2005b |
Serial |
616 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
A Robust Particle Filter-based Face Tracker Using a Combination of Color and Geometric Information |
Type |
Report |
| Year |
2005 |
Publication |
CVC Technical Report #90 |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
CVC (UAB) |
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Place of Publication |
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Editor |
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Original Title |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2005c |
Serial |
617 |
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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 |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
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| Address |
Albacete (Spain) |
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Thesis |
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Place of Publication |
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Editor |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2006b |
Serial |
714 |
| Permanent link to this record |
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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 |
Abbreviated Journal |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2006c |
Serial |
715 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Online Learning for Human-Robot Interaction |
Type |
Conference Article |
| Year |
2007 |
Publication |
IEEE Conference on Computer Vision and Pattern Recognition Workshop on |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Minneapolis (USA) |
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ISBN |
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Conference |
CVPR |
| Notes |
OR; MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2007a |
Serial |
791 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Incremental Subspace Learning for Cognitive Visual Processes |
Type |
Conference Article |
| Year |
2007 |
Publication |
Advances in Brain, Vision and Artificial Intelligence, 2nd International Symposium |
Abbreviated Journal |
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| Volume |
4729 |
Issue |
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Pages |
214–223 |
| Keywords |
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| Abstract |
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| Address |
Naples (Italy) |
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Thesis |
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Place of Publication |
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Editor |
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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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Expedition |
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Conference |
BVAI’07 |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2007b |
Serial |
901 |
| Permanent link to this record |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Learning to Learn: From Smarts Machines to Intelligent Machines |
Type |
Journal |
| Year |
2008 |
Publication |
Patter Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
29 |
Issue |
8 |
Pages |
1024–1032 |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2008a |
Serial |
950 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Online Nonparametric Discriminant Analysis for Incremental Subspace Learning and Recognition |
Type |
Journal |
| Year |
2008 |
Publication |
Pattern Analysis and Applications. Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications |
Abbreviated Journal |
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| Volume |
11 |
Issue |
3-4 |
Pages |
259–268 |
| Keywords |
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| Publisher |
Springer |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2008c |
Serial |
997 |
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| Author |
Bogdan Raducanu; Jordi Vitria |
| Title |
Face Recognition by Artificial Vision Systems: A Cognitive Perspective |
Type |
Journal |
| Year |
2008 |
Publication |
International Journal of Pattern Recognition and Artificial Intelligence |
Abbreviated Journal |
IJPRAI |
| Volume |
22 |
Issue |
5 |
Pages |
899–913 |
| Keywords |
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Series Title |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaV2008b |
Serial |
1007 |
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| Author |
Bogdan Raducanu; Jordi Vitria; Ales Leonardis |
| Title |
Online pattern recognition and machine learning techniques for computer-vision: Theory and applications |
Type |
Journal Article |
| Year |
2010 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
| Volume |
28 |
Issue |
7 |
Pages |
1063–1064 |
| Keywords |
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| Abstract |
(Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process. |
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Elsevier |
Place of Publication |
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Edition |
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| ISSN |
0262-8856 |
ISBN |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RVL2010 |
Serial |
1280 |
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| Author |
Bogdan Raducanu; Jordi Vitria; D. Gatica-Perez |
| Title |
You are Fired! Nonverbal Role Analysis in Competitive Meetings |
Type |
Conference Article |
| Year |
2009 |
Publication |
IEEE International Conference on Audio, Speech and Signal Processing |
Abbreviated Journal |
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Issue |
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Pages |
1949–1952 |
| Keywords |
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| Abstract |
This paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. For our study, we made use of ldquoThe Apprenticerdquo reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. The current study was carried out using nonverbal audio cues. Results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. |
| Address |
Taipei, Taiwan |
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Editor |
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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 |
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Series Issue |
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Edition |
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| ISSN |
1520-6149 |
ISBN |
978-1-4244-2353-8 |
Medium |
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Expedition |
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Conference |
ICASSP |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RVG2009 |
Serial |
1154 |
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