计算机与数字工程2017，Vol.45Issue(10)：2013-2017,5.DOI:10.3969/j.issn.1672-9722.2017.10.026
高斯核方向导数和RILPQ融合的人脸表情识别
Facial Expression Recognition Based on Gaussian Kernel Direction Derivative and RILPQ
摘要
Abstract
In view of the problem that the feature of facial expression recognition is not clear,this paper proposes a method of image feature extraction based on Gauss kernel direction derivative and RILPQ.In the RILPQ algorithm,the Gauss kernel multi di-rection derivative is introduced to form a filter,and the algorithm is applied to the expression data set of JAFFE data set.Experimen-tal results for the filter window radius of 11 pixels,the algorithm recognition rate is optimal,and higher than the LPQ algorithm, RLPQ algorithm recognition rate.At the same time,it is proved that the Gauss window radius and the direction of filtering have ef-fect on the recognition rate of the algorithm.关键词
人脸表情识别(FER)/旋转不变局部相位量化(RILPQ)/各向高斯核函数及方向导数/支持向量机(SVM)Key words
facial expression recognition(FER)/rotation invariant local phase quantization(RILPQ)/anisotropic Gauss-ian kernel function and directional derivative/support vector machine(SVM)分类
信息技术与安全科学引用本文复制引用
张鹏鹏,陈英,葛杨铭..高斯核方向导数和RILPQ融合的人脸表情识别[J].计算机与数字工程,2017,45(10):2013-2017,5.
