基于异向高斯核与RILPQ的模糊人脸表情识别方法

Blurred facial expression recognition method based on anisotropic Gaussian kernel and RILPQ

针对水平方向运动所造成的人脸图像模糊、边缘轮廓不清的问题,提出了一种改进的运动模糊人脸表情特征提取和识别方法。采用传统的时频估算法计算水平方向运动模糊长度;在各向异性高斯滤波器中重定义各向异性因子,形成椭圆形高斯窗;将新滤波器引入到旋转不变局部相位量化(RILPQ)算法的傅立叶变换以进行特征提取。针对JAFFE数据集的7种表情的实验结果表明:相对RILPQ,提出的方法能更为清晰地提取运动模糊人脸的表情特征,具有更高的识别率。

An improved method of motion fuzzy facial expression feature extraction and recognition is proposed to solve the problem of blur and unclear contour of facial image caused by horizontal motion. Traditional method of time frequency estimation is used to calculate the horizontal motion blur length. Anisotropic factor is redefined in anisotropic Gauss filter to form an elliptical Gauss window.The new filter is introduced into the Fourier transform of rotation invariant local phase quantization（RILPQ） algorithm for feature extraction.The experimental result based on JAFFE dataset shows that the proposed method not only can more clearly extract facial feature for motion blurred facial images,but also has higher recognition rate compared to the RILPQ algorithm.