Facial expression recognition based on Hessian regularized support vector machine

Authors:
Caifeng Song;Weifeng Liu;Yanjiang Wang
Affiliations:
China University of Petroleum (East China), Qingdao, P.R. China;China University of Petroleum (East China), Qingdao, P.R. China;China University of Petroleum (East China), Qingdao, P.R. China
Venue:
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Year:
2013

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Abstract

Semi-supervised learning (SSL) has achieved attractive performance in many pattern recognition areas including image annotation, object recognition, face recognition and facial expression recognition. The state of the art SSL algorithm is Laplacian regularization (LR) which determined the underlying manifold using graph Laplacian. However, LR suffers from the lack of extrapolating power which will be towards the constant function for the data points beyond the boundary of domain. In contrast to LR, Hessian regularization (HR) can well steer the function varying smoothly along the manifold. In this paper, we present Hessian regularized support vector machine (SVM) for facial expression recognition (FER). We carefully conduct experiments on JAFFE dataset. The experimental results show that HR based SVM (HesSVM) outperforms SVM and LR base SVM (LapSVM).