基于无参数二维判别局部保持投影算法的人脸识别  

Parameter-less two-dimensional discriminant locality preserving projections and face recognition

作　　者：龚劬[1] 王珂[1] 冉清华[1] 谷雅宁 

机构地区：[1]重庆大学数学与统计学院,重庆401331

出　　处：《计算机工程与应用》2016年第10期151-156,共6页Computer Engineering and Applications

摘　　要：通过向二维局部保持投影(2D-LPP)算法中引入类间约束和类标识信息,得到二维判别局部保持投影(2D-DLPP)算法,使它拥有更多的判别信息。但它却面临复杂的参数选择问题,这使得它在解决识别问题时受到限制。为解决此问题,构造无参数的相似矩阵,提出无参数的二维判别局部投影(无参数2D-DLPP)算法。在Yale和ORL人脸库上的仿真实验结果表明,该算法与二维判别局部保持投影(2D-DLPP)、二维局部保持投影法(2D-LPP)和二维线性判别分析法(2D-LDA)相比能够取得更高的识别率。By introducing between-class scatter constraint and label information into two-dimensional locality preserving projections（2D-LPP） algorithm, two-Dimensional Discriminant Locality Preserving Projections（2D-DLPP） has more discriminant power than 2D-LPP. However, 2D-DLPP is confronted with the difficulty of parameter selection, which limits its power on solving recognition problem. To solve this problem, by constructing parameter-less affinity matrix, an algorithm called parameter-less two-dimensional discriminant locality preserving projections（parameter-less 2D-DLPP）is proposed.The simulation results on Yale and ORL face database show that the method in this paper can get higher recognition rate than 2D-DLPP, 2D-LPP and 2D-LDA.

关 键 词：人脸识别 特征提取 二维判别局部保持投影 无参数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]