Bimodal 2D-3D face recognition using a two-stage fusion strategy

Aissaoui, Amel; Martinet, Jean

Document type :

Communication dans un congrès avec actes

DOI :

10.1109/IPTA.2015.7367146

Title :

Bimodal 2D-3D face recognition using a two-stage fusion strategy

Author(s) :

Aissaoui, Amel [Auteur]
Université des Sciences et de la Technologie Houari Boumediene = University of Sciences and Technology Houari Boumediene [Alger] [USTHB]
Martinet, Jean [Auteur]
Université de Lille, Sciences et Technologies
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Conference title :

International Conference on Image Processing Theory, Tools and Applications

City :

Orléans

Country :

France

Start date of the conference :

2015-11-10

Book title :

International Conference on Image Processing Theory, Tools and Applications

Journal title :

International Conference on Image Processing Theory, Tools and Applications

Publication date :

2015-11

English keyword(s) :

Face recognition
LBP
DLBP
Bimodal fusion

HAL domain(s) :

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

English abstract : [en]

This paper presents a novel approach for bimodal face recognition. In our approach, faces are represented by both texture and depth images. The well known Local Binary Pattern (LBP) is used to describe the texture images. ...
Show more >This paper presents a novel approach for bimodal face recognition. In our approach, faces are represented by both texture and depth images. The well known Local Binary Pattern (LBP) is used to describe the texture images. The depth faces representation is based on the Depth Local Binary Pattern, which is an extension of the the LBP descriptor allowing more discriminative power of smooth depth images. In order to perform the bimodal face recognition, a two-stage fusion scheme is proposed. It allows to take advantage of the complementarity of range and texture modalities at both descriptor (early fusion) and decision (late fusion) levels. We have conducted extensive experiments on several datasets in order to evaluate our approach. The obtained results show that our combination of texture and depth descriptors yields higher results than when taken separately or using an early/late fusion scheme.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

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