We investigate the problem of facial expression recognition using 3D face data. Our approach is based on local shape analysis of several relevant regions of a given face scan. These regions or patches from facial surfaces are extracted and represented by sets of closed curves. A Riemannian framework is used to derive the shape analysis of the extracted patches. The applied framework permits to calculate a similarity (or dissimilarity) distances between patches, and to compute the optimal deformation between them. Once calculated, these measures are employed as inputs to a commonly used classification techniques such as AdaBoost and Support Vector Machines (SVM). A quantitative evaluation of our novel approach is conducted on a subset of the publicly available BU-3DFE database.

Local 3D Shape Analysis for Facial Expression Recognition / A. Maalej; B. Ben Amor; M. Daoudi; A. Srivastava; S. Berretti. - STAMPA. - .(2010), pp. 4129-4132. ((Intervento presentato al convegno 20th International Conference on Pattern Recognition tenutosi a Istanbul, Turkey nel August 23-26 [10.1109/ICPR.2010.1003].

Local 3D Shape Analysis for Facial Expression Recognition

BERRETTI, STEFANO
2010

Abstract

We investigate the problem of facial expression recognition using 3D face data. Our approach is based on local shape analysis of several relevant regions of a given face scan. These regions or patches from facial surfaces are extracted and represented by sets of closed curves. A Riemannian framework is used to derive the shape analysis of the extracted patches. The applied framework permits to calculate a similarity (or dissimilarity) distances between patches, and to compute the optimal deformation between them. Once calculated, these measures are employed as inputs to a commonly used classification techniques such as AdaBoost and Support Vector Machines (SVM). A quantitative evaluation of our novel approach is conducted on a subset of the publicly available BU-3DFE database.
Pattern Recognition (ICPR), 2010 20th International Conference on
20th International Conference on Pattern Recognition
Istanbul, Turkey
August 23-26
A. Maalej; B. Ben Amor; M. Daoudi; A. Srivastava; S. Berretti
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2158/394825
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