关键词: 东亚人脸表情识别, 流形学习, 二维线性判别保局分析（2D-LDLPA）特征提取, 随机森林分类

Abstract: Extracting facial expression features accurately and designing the superior performance classifier are the two critical problems in the field of facial expression recognition, and the recognition is more challenge for the East Asian expression who are famous for implicit. In order to solve this problem, the Two-Dimensional Linear Discriminate Locality Preserving Analysis（2D-LDLPA） algorithm based on image based projection is firstly proposed to directly extract features on image matrix. Then, through constructing the decision trees to learn the extracted expression features, the random forest classifier is applied to improve the accurate ratio of the East Asian facial expression recognition. Finally, the recognition accuracy and computational efficiency of the proposed algorithm are verified by the experiments on two East Asian facial expression databases.

Key words: East Asian facial expression recognition, manifold learning, Two-Dimensional Linear Discriminate Locality Preserving Analysis（2D-LDLPA） feature extraction, random forest classification