基于双线性模型的人脸表情识别技术

针对现阶段人脸表情识别过程中所遇到的问题，基于三维数据库BU-3DFE中的三维表情数据，研究三维人脸表情数据的点云对齐及基于对齐数据的双线性模型建立，对基于双线性模型的识别算法加以改进，形成新的识别分类算法，降低原有算法中身份特征参与计算的比重，最大可能地降低身份特征对于整个表情识别过程的影响。旨在提高表情识别的结果，最终实现高鲁棒性的三维表情识别。

Facial Expression Recognition Techniques Based on Bilinear Model

Aiming at the problems existing in facial expression recognition currently , based on the data in the 3D expression data-base BU-3DFE, we study the point cloud alignment of 3D facial expression data , establish the bilinear models based on the align-ment data , and improve the recognition algorithms based on bilinear model in order to form the new recognition and classification algorithms, to reduce the quantity of identity feature calculation in original algorithm , to minimize the influence of identity feature on the total expression recognition process , to improve the results of facial expression recognition , and to ultimately achieve the high robustness of 3D facial expression recognition .