结合Gabor变换和FastICA的人脸表情识别方法  

Facial expression recognition based on Gabor transform and FastICA

作　　者：丁维福[1] 姜威[1] 张亮亮[1] 

机构地区：[1]山东大学信息科学与工程学院,济南250100

出　　处：《计算机工程与应用》2011年第24期178-181,共4页Computer Engineering and Applications

摘　　要：提出了一种结合Gabor变换和FastICA技术的人脸表情特征提取方法。Gabor小波具有很好的空频局部性和多方向选择性,因此更有利于表情细节信息的提取。FastICA技术能够消除信号间的高阶统计冗余。对图像进行Gabor变换,把得到的系数排列成Gabor特征矢量,用FastICA对Gabor特征矢量进行特征提取,用K-近邻分类器进行分类。JAFFE表情库中的实验证明该方法的有效性。An effective method for the facial expression feature extraction is presented by combining the Gabor transform with the Fast Independent Component Analysis（FastICA）.Gabor wavelets exhibit strong characteristics of spatial locality and orienta-tion selectivity,which are good for the extraction of the image’s texture.FastICA can reduce the redundancy of high-order statis-tics.The Gabor transform is carried out on each original image,and the outputs are concatenated into a Gabor feature vector.Fas-tICA approach is used to extract features from the Gabor feature vectors of all the images.The K-neighbor method is used for classification.A series of experiments performed on the JAFFE database indicate the efficiency of the proposed method.

关 键 词：表情识别 特征提取 GABOR变换 快速独立成分分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]