Title :

Fully Automatic 3D Facial Expression Recognition using Differential Mean Curvature Maps and Histograms of Oriented Gradients

Author(s) :

Lemaire, Pierre [Auteur]
Extraction de Caractéristiques et Identification [imagine]
Chen, Liming [Auteur]
Extraction de Caractéristiques et Identification [imagine]
Ardabilian, Mohsen [Auteur]
Extraction de Caractéristiques et Identification [imagine]
Daoudi, Mohamed [Auteur]
FOX MIIRE [LIFL]

Conference title :

Workshop 3D Face Biometrics, IEEE Automatic Facial and Gesture Recognition

City :

Shanghai

Country :

Chine

Start date of the conference :

2013-04-22

Publication date :

2013-04-22

HAL domain(s) :

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

English abstract : [en]

In this paper, we propose an holistic, fully auto- matic approach to 3D Facial Expression Recognition (FER). A novel facial representation, namely Differential Mean Curva- ture Maps (DMCMs), is proposed to capture both ...
Show more >In this paper, we propose an holistic, fully auto- matic approach to 3D Facial Expression Recognition (FER). A novel facial representation, namely Differential Mean Curva- ture Maps (DMCMs), is proposed to capture both global and local facial surface deformations which typically occur during facial expressions. These DMCMs are directly extracted from 3D depth images, by calculating the mean curvatures thanks to an integral computation. To account for facial morphology variations, they are further normalized through an aspect ratio deformation. Finally, Histograms of Oriented Gradients (HOG) are applied to regions of these normalized DMCMs and allow for the generation of facial features that can be fed to the widely used Multiclass-SVM classification algorithm. Using the protocol proposed by Gong et al. on the BU-3DFE dataset, the proposed approach displays competitive performance while staying entirely automatic.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

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

Source :

Harvested from HAL