3D Face Recognition Under Expressions,Occlusions ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
3D Face Recognition Under Expressions,Occlusions and Pose Variations
Auteur(s) :
Drira, Hassen [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Ben Amor, Boulbaba [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Anuj, Srivastava [Auteur]
Department of Statistics [Tallahassee, FL]
Daoudi, Mohamed [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Slama, Rim [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Ben Amor, Boulbaba [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Anuj, Srivastava [Auteur]
Department of Statistics [Tallahassee, FL]
Daoudi, Mohamed [Auteur]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Slama, Rim [Auteur]
FOX MIIRE [LIFL]
Titre de la revue :
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pagination :
2270 - 2283
Éditeur :
Institute of Electrical and Electronics Engineers
Date de publication :
2013-02-21
ISSN :
0162-8828
Mot(s)-clé(s) en anglais :
3D face recognition
shape analysis
biometrics
quality control
data restoration
shape analysis
biometrics
quality control
data restoration
Discipline(s) HAL :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Sciences de l'Homme et Société/Psychologie
Sciences de l'Homme et Société/Psychologie
Résumé en anglais : [en]
We propose a novel geometric framework for analyzing 3D faces, with the specific goals of comparing, matching, and averaging their shapes. Here we represent facial surfaces by radial curves emanating from the nose tips and ...
Lire la suite >We propose a novel geometric framework for analyzing 3D faces, with the specific goals of comparing, matching, and averaging their shapes. Here we represent facial surfaces by radial curves emanating from the nose tips and use elastic shape analysis of these curves to develop a Riemannian framework for analyzing shapes of full facial surfaces. This representation, along with the elastic Riemannian metric, seems natural for measuring facial deformations and is robust to challenges such as large facial expressions (especially those with open mouths), large pose variations, missing parts, and partial occlusions due to glasses, hair, etc. This framework is shown to be promising from both - empirical and theoretical - perspectives. In terms of the empirical evaluation, our results match or improve the state-of-the-art methods on three prominent databases: FRGCv2, GavabDB, and Bosphorus, each posing a different type of challenge. From a theoretical perspective, this framework allows for formal statistical inferences, such as the estimation of missing facial parts using PCA on tangent spaces and computing average shapes.Lire moins >
Lire la suite >We propose a novel geometric framework for analyzing 3D faces, with the specific goals of comparing, matching, and averaging their shapes. Here we represent facial surfaces by radial curves emanating from the nose tips and use elastic shape analysis of these curves to develop a Riemannian framework for analyzing shapes of full facial surfaces. This representation, along with the elastic Riemannian metric, seems natural for measuring facial deformations and is robust to challenges such as large facial expressions (especially those with open mouths), large pose variations, missing parts, and partial occlusions due to glasses, hair, etc. This framework is shown to be promising from both - empirical and theoretical - perspectives. In terms of the empirical evaluation, our results match or improve the state-of-the-art methods on three prominent databases: FRGCv2, GavabDB, and Bosphorus, each posing a different type of challenge. From a theoretical perspective, this framework allows for formal statistical inferences, such as the estimation of missing facial parts using PCA on tangent spaces and computing average shapes.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
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