The effects of Pose on Facial Expression Recognition | Zendy

Stephen Moore | Zendy; Richard Bowden | Zendy

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The effects of Pose on Facial Expression Recognition

Author(s) -

Stephen Moore,

Richard Bowden

Publication year - 2009

Publication title -

surrey open research repository (university of surrey)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.23.79

Subject(s) - local binary patterns , facial expression , artificial intelligence , pattern recognition (psychology) , support vector machine , computer science , three dimensional face recognition , expression (computer science) , facial expression recognition , facial recognition system , computer vision , image (mathematics) , histogram , face detection , programming language

Research into facial expression recognition has predominantly been based upon near frontal view data. However, a recent 3D facial expression database (BU-3DFE database) has allowed empirical investigation of facial expression recognition across pose. In this paper, we investigate the effects of pose from frontal to profile view on facial expression recognition. Experiments are carried out on 100 subjects with 5 yaw angles over 6 prototypical expressions. Expressions have 4 levels of intensity from subtle to exaggerated. We evaluate features such as local binary patterns (LBPs) as well as various extensions of LBPs. In addition, a novel approach to facial expression recognition is proposed using local gabor binary patterns (LGBPs). Multi class support vector machines (SVMs) are used for classification. We investigate the effects of image resolution and pose on facial expression classification using a variety of different features

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