一种基于几何特征的表情相似性度量方法

A Similarity Measurement Method of Facial Expression Based on Geometric Features

在表演驱动、表情克隆等人脸动画中,需要寻找最相似表情以提高动画真实感和逼真度.基于面部表情几何特征提出一种特征加权的表情相似性度量方法.首先,在主动外观模型上,利用链码描述各区域的形状特征以刻画局部表情细节,并根据区域特征点间的拓扑关系构建形变特征以反映整体表情信息.然后,采用特征加权方式对融合的几何特征进行相似性度量,并将权重的求解过程转化为加权目标函数最小化.最后,利用求解的权重以及特征加权函数度量表情间的相似性,寻找与之最相似的表情图像.在BU-3DFE数据库和FEEDTUM数据库上的实验结果表明,该方法在寻找相似表情的正确率方面明显高于现有的度量方法,并且对不同类型、不同强度的表情描述保持较好鲁棒性,尤其在嘴型、脸颊收缩、嘴开合幅度等表情细节维持较高相似度.

In facial animations such as performance-driven and expression cloning, it needs to find the most similar expression to enhance the reality and fidelity of animations. A feature-weighted expression similarity measurement method is proposed based on facial geometric features. Firstly, chain code is used to characterize shape features for local expression regions, meanwhile deformation features are built based on topological relations among regional feature points to reflect holistic expression information. Then, feature-weighted method is adopted to measure the similarities of fused geometric features, and the solving process of feature weights is transformed to minimizing process of the weighted objective function. Finally, the solved weights as well as feature weighting functions are performed to measure similarities between two expressions and seek the most similar image with a input expression image. The experimental results on BU-3DFE database and FEEDTUM database show that the proposed method has significantly higher accuracy in seeking similar expressions than existing measurement methods, and it keeps better robustness for the expressions with different categories and different intensities, especially in local details such as the shape of mouth, the contraction of cheek, and the open-close amplitude of mouth.