基于图像优化局部保留投影的人脸表情识别  

Facial expression recognition based on graph-optimized locality preserving projections

作　　者：黄勇[1] 

机构地区：[1]柳州铁道职业技术学院电子工程系,广西柳州545007

出　　处：《计算机工程与应用》2011年第27期210-211,215,共3页Computer Engineering and Applications

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.

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 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]