关键词: Gabor小波变换, 表情特征提取, Fisher线性判别分析, 支持向量机

Abstract: A local Gabor wavelet facial expression recognition algorithm based on automatic segmentation to the still image containing facial expression information was introduced. Firstly, mathematical morphology combined with projection was used to locate the brow and eye region, and the mouth region was located by calculating template average, which can segment the expression sub-regions automatically. Secondly, features of the expression sub-regions were extracted by Gabor wavelet transformation and then effective Gabor expression features were selected by Fisher Linear Discriminant (FLD) analysis, removing the redundancy and relevance of expression features. Finally the features were sent to Support Vector Machine (SVM) to classify different expressions. The algorithm was tested on Japanese female facial expression database. It is easy to realize automation. The feasibility of this method has been verified by experiments.

Key words: Gabor wavelet transformation, expression feature extraction, Fisher Linear Discriminant （FLD） analysis, Support Vector Machine (SVM)