Title :

3D Dynamic Expression Recognition Based on a Novel Deformation Vector Field and Random Forest

Author(s) :

Hassen, Drira [Auteur]
FOX MIIRE [LIFL]
Ben Amor, Boulbaba [Auteur]
FOX MIIRE [LIFL]
Mohamed, Daoudi [Auteur]
FOX MIIRE [LIFL]
Anuj, Srivastava [Auteur]
Department of Statistics [Tallahassee, FL]
Berretti, Stefano [Auteur]
Dipartimento di Sistemi e Informatica [DSI]

Conference title :

21st International Conference on Pattern Recognition

City :

Tsukuba

Country :

Japon

Start date of the conference :

2012-11-11

Book title :

21st International Conference on Pattern Recognition

Publication date :

2012-11-11

HAL domain(s) :

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

English abstract : [en]

This paper proposes a new method for facial motion extraction to represent, learn and recognize observed expressions, from 4D video sequences. The approach called Deformation Vector Field (DVF) is based on Riemannian facial ...
Show more >This paper proposes a new method for facial motion extraction to represent, learn and recognize observed expressions, from 4D video sequences. The approach called Deformation Vector Field (DVF) is based on Riemannian facial shape analysis and captures densely dynamic information from the entire face. The resulting temporal vector field is used to build the feature vector for expression recognition from 3D dynamic faces. By applying LDA-based feature space transformation for dimensionality reduction which is followed by a Multiclass Random Forest learning algorithm, the proposed approach achieved 93% average recognition rate on BU-4DFE database and outperforms state-of-art approaches.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