An experimental illustration of 3D facial ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
An experimental illustration of 3D facial shape analysis under facial expressions
Auteur(s) :
Ben Amor, Boulbaba [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
Drira, Hassen [Auteur]
FOX MIIRE [LIFL]
Ballihi, Lahoucine [Auteur]
Laboratoire de Recherche en Informatique et Télécommunications [Rabat] [GSCM-LRIT]
FOX MIIRE [LIFL]
Srivastava, Anuj [Auteur]
Department of Statistics [Tallahassee, FL]
Daoudi, Mohamed [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
Drira, Hassen [Auteur]
FOX MIIRE [LIFL]
Ballihi, Lahoucine [Auteur]
Laboratoire de Recherche en Informatique et Télécommunications [Rabat] [GSCM-LRIT]
FOX MIIRE [LIFL]
Srivastava, Anuj [Auteur]
Department of Statistics [Tallahassee, FL]
Daoudi, Mohamed [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
Titre de la revue :
Annals of Telecommunications - annales des télécommunications
Pagination :
369-379
Éditeur :
Springer
Date de publication :
2009
ISSN :
0003-4347
Mot(s)-clé(s) en anglais :
Facial shape analysis
3D Face recognition
automatic preprocessing
3D Face recognition
automatic preprocessing
Discipline(s) HAL :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Résumé en anglais : [en]
The main goal of this paper is to illustrate a geometric analysis of 3D facial shapes in presence of varying facial expressions. This approach consists of the following two main steps: (i) Each facial surface is automatically ...
Lire la suite >The main goal of this paper is to illustrate a geometric analysis of 3D facial shapes in presence of varying facial expressions. This approach consists of the following two main steps: (i) Each facial surface is automatically denoised and preprocessed to result in an indexed collection of facial curves. During this step one detects the tip of the nose and defines a surface distance function with that tip as the reference point. The level curves of this distance function are the desired facial curves. (ii) Comparisons between faces are based on optimal deformations from one to another. This, in turn, is based on optimal deformations of the corresponding facial curves across surfaces under an elastic metric. The experimental results, generated using a subset of FRGC (Face Recognition Grand Challenge) v2 dataset, demonstrate the success of the proposed framework in recognizing people under different facial expressions. The recognition rates obtained here exceed those for a baseline ICP algorithm on the same dataset.Lire moins >
Lire la suite >The main goal of this paper is to illustrate a geometric analysis of 3D facial shapes in presence of varying facial expressions. This approach consists of the following two main steps: (i) Each facial surface is automatically denoised and preprocessed to result in an indexed collection of facial curves. During this step one detects the tip of the nose and defines a surface distance function with that tip as the reference point. The level curves of this distance function are the desired facial curves. (ii) Comparisons between faces are based on optimal deformations from one to another. This, in turn, is based on optimal deformations of the corresponding facial curves across surfaces under an elastic metric. The experimental results, generated using a subset of FRGC (Face Recognition Grand Challenge) v2 dataset, demonstrate the success of the proposed framework in recognizing people under different facial expressions. The recognition rates obtained here exceed those for a baseline ICP algorithm on the same dataset.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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