Facial Expression Synthesis Based on Facial Expression Decomposition and Warping
基于表情分解-扭曲变形的人工表情合成算法

This paper proposes a robust algorithm of facial expression synthesis.Decompose a train set into person subspace,expression subspace and feature subspace by employing higher-order singular value decomposition(HOSVD),and then map them to expression subspace,which can be used to synthesize an expressive image of arbitrary strength,given any frontal facial image.By warping source image to generate the target image rather than by linear-combining the images in train set as usual,this approach not only lessens the train set data storage and the computation complexity,but also enables the system to cope with facial images of arbitrary size,background,illumination condition,coloration or pose.With square interpolation,expression facial images of any assigned strength can be obtained.Experiments prove that this algorithm has higher efficiency and can generate very excellent images.