Person Independent 3D Facial Expression Recognition by a Selected Ensemble of SIFT Descriptors

Berretti, Stefano; Amor, Boulbaba Ben; Daoudi, Mohamed; Bimbo, Alberto Del

Person Independent 3D Facial Expression Recognition by a Selected Ensemble of SIFT Descriptors

Files

047-054.pdf (355.01 KB)

Date

2010

Authors

Berretti, Stefano
Amor, Boulbaba Ben
Daoudi, Mohamed
Bimbo, Alberto Del

Publisher

The Eurographics Association

Abstract

Facial expression recognition has been addressed mainly working on 2D images or videos. In this paper, the problem of person-independent facial expression recognition is addressed on 3D shapes. To this end, an original approach is proposed that relies on selecting the minimal-redundancy maximal-relevance features derived from a pool of SIFT feature descriptors computed in correspondence with facial landmarks of depth images. Training a Support Vector Machine for every basic facial expression to be recognized, and combining them to form a multiclass classifier, an average recognition rate of 77.5% on the BU-3DFE database has been obtained. Comparison with competitors approaches using a common experimental setting on the BU-3DFE database, shows that our solution is able to obtain state of the art results.

        @inproceedings{:10.2312/3DOR/3DOR10/047-054
,
booktitle = {Eurographics Workshop on 3D Object Retrieval
},
editor = {Mohamed Daoudi and Tobias Schreck
},
title = {{Person Independent 3D Facial Expression Recognition by a Selected Ensemble of SIFT Descriptors
}},
author = {Berretti, Stefano and 
Amor, Boulbaba Ben and 
Daoudi, Mohamed and 
Bimbo, Alberto Del
},
year = {2010
},
publisher = {The Eurographics Association
},
ISSN = {1997-0471
},
ISBN = {978-3-905674-22-4
},
DOI = {/10.2312/3DOR/3DOR10/047-054
}
}