ABSTRACT In recent years, a growing interest has been created for improvement of human interaction with computers. Hence, automatic recognition of facial expressions has become one of the active research topics. The purpose of this paper is to identify facial expressions, by using differential geometric features. In the proposed method, only the first and last images are used and differential features are extracted from these two images. Differential geometric features are extracted from changes in the important points of the face in the two images. In this method, the distance between the important points of the face and the reference point was calculated in both directions x and y, for two images, and with the difference between the distance, the differential geometric features between the two images were obtained. Based on the results, with this method, recognition accuracy of six facial expressions in the database was 96.44%, CK +.

中文翻译：

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基于微分几何特征的面部表情识别

摘要 近年来，人们对改进人机交互的兴趣日益浓厚。因此，面部表情的自动识别已成为活跃的研究课题之一。本文的目的是通过使用微分几何特征来识别面部表情。在所提出的方法中，仅使用第一张和最后一张图像，并从这两张图像中提取差异特征。从两幅图像中人脸重要点的变化中提取微分几何特征。该方法对两幅图像分别计算人脸重要点与参考点在x、y两个方向上的距离，利用距离的差值得到两幅图像之间的微分几何特征。根据结果​​，