摘要
面部表情是一种非语言暗示,在人际交往关系中发挥重要的作用。静态图像中分析处理面部表情,人机交互的处理方法就有很多。首先利用Gabor对静态图像进行特征提取,由PCA降维之后再用贝叶斯估计参数构建的贝叶斯分类器进行分类,从而达到表情识别的目的。
Facial expressions convey non-verbal cues,which play an important role in interpersonal relations.For recognizing the facial expression from facial images,a number of approaches in the field of human computer interaction can be founded. At first,by using Gabor feature extraction from still images,then,PCA dimensionality before classification with the construction of Bayesian estimation-Bayesian .classifier,so as to achieve the purpose of facial expression recognition in this paper.
出处
《工业控制计算机》
2013年第11期114-114,118,共2页
Industrial Control Computer
关键词
表情识别
贝叶斯分类器
参数估计
Gabor特征提取
expression recognition,bayesian classifier,parameter estimation,Gabor feature extraction
