摘要
提出了一种基于图像优化局部保留投影的人脸表情识别方法。该算法在降维过程中将图像结构信息融入到LPP目标函数中,称之为GOLPP。与LPP不同,GOLPP通过降维处理,获得图像结构信息的同时将投影最优化,这样可从原始表情数据中提取更具判决性的表情信息。基于JAFFE和CED-WYU(1.0)两个表情数据库的识别结果表明,基于GOLPP的特征提取方法能有效地提高识别率。
A facial expression recognition method based on Graph-Optimized Locality Preserving Projections（GOLPP） is proposed in this paper.Unlike LPP,GOLPP incorporates graph construction into the LPP objective function in dimension reduction process,thus obtains a simultaneous learning framework for graph construction and projection optimization,GOLPP can extract more useful and discriminatal expression features from the original expression data.Experimental result on JAFFE and CED-WYU show that GOLPP is an effective method for improving the recognition accuracy.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第27期210-211,215,共3页
Computer Engineering and Applications
关键词
局部保留投影
图像优化局部保留投影
人脸表情识别
Locality Preserving Projections（LPP）
Graph-Optimized Locality Preserving Projections（GOLPP）
facial expression recognition
