基于贝叶斯优化算法的脸面特征向量子集选择  

Eigenvector Subset Selection Using Bayesian Optimization Algorithm

作　　者：郭卫锋[1] 林亚平[1] 罗光平[1] 

机构地区：[1]湖南大学计算机系,长沙410082

出　　处：《计算机科学》2002年第12期162-163,194,共3页Computer Science

基　　金：国家教育部科学技术重点研究项目(99092)

摘　　要：Eigenvector subset selection is the key to face recognition. In this paper ,we propose ESS-BOA, a newrandomized, population-based evolutionary algorithm which deals with the Eigenvector Subset Selection (ESS)prob-lem on face recognition application. In ESS-BOA ,the ESS problem, stated as a search problem ,uses the BayesianOptimization Algorithm (BOA) as searching engine and the distance degree as the object function to select eigenvec-tor. Experimental results show that ESS-BOA outperforms the traditional the eigenface selection algorithm.Eigenvector subset selection is the key to face recognition. In this paper , we propose ESS-BOA, a new randomized, population-based evolutionary algorithm which deals with the Eigenvector Subset Selection (ESS )prob-lem on face recognition application. In ESS-BOA ,the ESS problem, stated as a search problem ,uses the Bayesian Optimization Algorithm (BOA) as searching engine and the distance degree as the object function to select eigenvector. Experimental results show that ESS-BOA outperforms the traditional the eigenface selection algorithm.

关 键 词：人脸识别 脸面特征向量子集选择 贝叶斯优化算法 图像分析 图像理解 计算机 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]