Multi patches 3D facial representation for Person Authentication using AdaBoost

Ballihi, Lahoucine; Ben Amor, Boulbaba; Daoudi, Mohamed; Srivastava, Anuj

Type de document :

Communication dans un congrès avec actes

Titre :

Multi patches 3D facial representation for Person Authentication using AdaBoost

Auteur(s) :

Ballihi, Lahoucine [Auteur]
Laboratoire de Recherche en Informatique et Télécommunications [Rabat] [GSCM-LRIT]
FOX MIIRE [LIFL]
Ben Amor, Boulbaba [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Daoudi, Mohamed [Auteur]

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Srivastava, Anuj [Auteur]
Department of Statistics [Tallahassee, FL]

Titre de la manifestation scientifique :

I/V Communications and Mobile Network (ISVC), 2010 5th International Symposium on

Ville :

Rabat

Pays :

Maroc

Date de début de la manifestation scientifique :

2010-09-30

Titre de l’ouvrage :

I/V Communications and Mobile Network (ISVC), 2010 5th International Symposium on

Date de publication :

2010-09-30

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

In this paper, we investigate the(problem of 3D face authentification) use of AdaBoost-based learning lgorithm which select the relevent curves in the face.We use the shape of 3D curve for face authentication. The basic ...
Lire la suite >In this paper, we investigate the(problem of 3D face authentification) use of AdaBoost-based learning lgorithm which select the relevent curves in the face.We use the shape of 3D curve for face authentication. The basic idea is the analysis of the shape of local facial set of cuves. The set of curves are extracted using level curves based representation centered on facial feature point landmarks. We apply our framework to study and compare this set through the computation of the geodesic distance between corresponding curves on different 3D facial models. AdaBoost considers each curve as a weak classifier and selects iteratively relevant curves and show that there is significant improvement in results. The effectiveness of this technique is evaluated on a subset taken from BU-3DFE(3D Facial Expression Database - Binghamton University) database. The proposed approach increase authentication performances using AdaBoost classifier compared to a simple fusion of scores from all curves.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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ISVC2010.pdf
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