一种用于人脸识别的正交邻域保护嵌入算法  

Orthogonal neighborhood preserving embedding algorithm for face recognition

作　　者：陶晓燕[1] 姬红兵[1] 景志宏[1] 

机构地区：[1]西安电子科技大学电子工程学院,陕西西安710071

出　　处：《西安电子科技大学学报》2008年第3期439-443,共5页Journal of Xidian University

基　　金：国家部委基金资助

摘　　要：在邻域保护嵌入算法的基础上，提出了一种新的降维方法——正交邻域保护嵌入算法．首先，从最优投影的概念出发，定义了一种反映投影向量的邻域结构保护能力的函数；然后以邻域保护函数为目标函数，在原始的优化问题中增加正交约束条件，推导得到一组具有正交性的最优投影向量的迭代公式．与邻域保护嵌入算法相比，得到的正交向量具有更好的邻域保护性能，从而带来更强的判别能力，降低了误差率．在标准人脸库上的实验结果表明，与其他降维方法相比，新算法的最低误差率可减小15％～20％，且在选取的特征维数较低时就可获得最优值．Based on the Neighborhood Preserving Embedding （NPE） algorithm, a novel dimensionality reduction method called ONPE is proposed. First, a function which reflects the locality preserving power of the projective vectors is defined. Then, with the neighborhood preserving function as the objective function and the orthogonal constrained conditions added to the original optimal problem, the iterative formulae for finding a set of orthogonal optimal projection vectors are deduced. Compared with the NPE algorithm, the orthogonal vectors have the better locality preserving power, and thus the stronger discriminant power can be obtained and the error rate reduced. Experimental results on the standard face databases illustrate that in comparison with the other dimensionality reduction methods, the lowest error rate of the new method can be reduced by 15%～ 20% and can be achieved when the number of the selected features is comparatively small.

关 键 词：邻域保护嵌入算法 正交邻域保护嵌入算法 邻域保护能力 人脸识别 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]