3D Facial expression recognition based on histograms of surface differential quantities

Authors:
Huibin Li;Jean-Marie Morvan;Liming Chen
Affiliations:
Université de Lyon, CNRS and Ecole Centrale de Lyon, LIRIS UMR5205, Lyon, France;Université de Lyon, CNRS and Université Lyon, Institut Camille Jordan, Villeurbanne - Cedex, France and King Abdullah University of Science and Technology, Saudi Arabia;Université de Lyon, CNRS and Ecole Centrale de Lyon, LIRIS UMR5205, Lyon, France
Venue:
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Year:
2011

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Abstract

3D face models accurately capture facial surfaces, making it possible for precise description of facial activities. In this paper, we present a novel mesh-based method for 3D facial expression recognition using two local shape descriptors. To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle theory based curvature estimation method is employed on 3D face models along with the common cubic fitting curvature estimation method for the purpose of comparison. Based on the basic fact that different expressions involve different local shape deformations, the SVM classifier with both linear and RBF kernels outperforms the state of the art results on the subset of the BU-3DFE database with the same experimental setting.