A comprehensive statistical framework for elastic shape analysis of 3D faces

Kurtek, Sebastian; Drira, Hassen

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1016/j.cag.2015.05.027

Titre :

A comprehensive statistical framework for elastic shape analysis of 3D faces

Auteur(s) :

Kurtek, Sebastian [Auteur]
The Ohio State University [Columbus] [OSU]
Drira, Hassen [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut Mines-Télécom [Paris] [IMT]

Titre de la revue :

Computers and Graphics

Pagination :

52-59

Éditeur :

Elsevier

Date de publication :

2015

ISSN :

0097-8493

Mot(s)-clé(s) en anglais :

3D face
statistical framework
elastic Riemannian metric
generative face model

Discipline(s) HAL :

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

Résumé en anglais : [en]

We develop a comprehensive statistical framework for analyzing shapes of 3D faces. In particular, we adapt a recent elastic shape analysis framework to the case of hemispherical surfaces, and explore its use in a number ...
Lire la suite >We develop a comprehensive statistical framework for analyzing shapes of 3D faces. In particular, we adapt a recent elastic shape analysis framework to the case of hemispherical surfaces, and explore its use in a number of processing applications. This framework provides a parameterization-invariant, elastic Riemannian metric, which allows the development of mathematically rigorous tools for statistical analysis. Specifically, this paper describes methods for registration, comparison and deformation, averaging, computation of covariance and summarization of variability using principal component analysis, random sampling from generative shape models, symmetry analysis, and expression and identity classification. An important aspect of this work is that all tasks are preformed under a unified metric, which has a natural interpretation in terms of bending and stretching of one 3D face to align it with another. We use a subset of the BU-3DFE face dataset, which contains varying magnitudes of expression.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :