Expression decomposition algorithm based on appearance manifolds
Luo Da-yong · Computer Engineering and Applications Journal · 2008
In this paper,expression decomposition algorithm based on appearance manifolds is proposed.Firstly,face images are mapped into low-dimensional manifold subspace using Locality Preserving Projections(LPP).Secondly,these low-dimensional representations are decomposed into person subspace and facial expression subspace.Finally,face and facial expression recognition are realized.The problem of image feature extraction in higher-order singular value decomposition is solved by using appearance manifolds learning method.By applying Higher-Order Singular Value Decomposition(HOSVD) to appearance manifolds,person pattern hardly influence facial expression recognition.The advantages of higher-order singular value decomposition and manifolds learning are fused effectively.The algorithm is tested on JAFFE and CMP-AMP face database.The experimental result shows that it is powerful and effective for face and facial recognition.