张量描述下的多姿态多表情人脸合成方法

为了从一幅人脸图像中合成出该人脸其他姿态和表情下的图像，提出了一种基于张量子空间的多姿态人脸表情合成方法。首先，用标记过特征点的人脸图像集构造四维纹理特征张量和形状张量；其次，通过张量分解得到核张量以及各维的投影子空间(人物标识、表情、姿态、特征维)；最后应用核张量以及表情、姿态子空间构造新的张量用于姿态、表情的合成，在合成新人脸图像的时候充分利用了影响人脸的各因素间的内在关系。实验结果表明，所提方法可以利用一张已知表情和姿态的人脸图合成出自然合理的其他姿态表情下的该人脸图像。

Multi-pose and expression face synthesis method based on tensor representation

To synthesize facial pose and expression images simultaneously from one image, a tensor-based subspace projection method for synthesizing multi-pose and expression face images was proposed. Firstly, the forth order texture tensor and shape tensor were created from the feature annotated images respectively. Then a tucker tensor decomposition technique was applied to build projection subspaces (person, expression, pose and feature subspaces). Core tensors, expressions, poses and feature subspaces were organized into a new tensor properly which was used for synthesizing new facial poses and expressions. The proposed method took full advantage of the intrinsic relationship among the facial affected various factors. The experimental results show that the proposed method can synthesize different facial expressions with kinds of poses of the face using a known facial expression and pose image.