火力与指挥控制2017，Vol.42Issue(4)：29-32,4.
基于稀疏子空间聚类的人脸识别方法
Face Recognition Method Based on Sparse Subspace Clustering
摘要
Abstract
We offer two kinds of sparse subspace clustering optimization algorithm,sparse linear space clustering and sparse affine subspace clustering,based on the existing theory of sparse subspace clustering algorithm. For different data gathering,these two kinds of optimization algorithm has different clustering results. In this paper,different sparse coefficient matrix by sparse expression is obtained. In order to achieve cluster,the sparse coefficient matrix is applied to relatively simple regularization of spectral clustering algorithm. Application of Yale B data ,we recognize and classify face image :using sparse linear space clustering algorithm is better than the sparse affine subspace clustering algorithm;Comparing with the traditional sparse subspace clustering ,it is more fast and efficient in the time of execution and error rate of algorithm.关键词
子空间聚类/稀疏子空间聚类/谱聚类算法/人脸识别Key words
subspace clustering/sparse subspace clustering/spectral clustering algorithms/face regulation分类
信息技术与安全科学引用本文复制引用
张彩霞,胡红萍,白艳萍..基于稀疏子空间聚类的人脸识别方法[J].火力与指挥控制,2017,42(4):29-32,4.基金项目
国家自然科学基金(61275120) （61275120）
2014年校自然科学基金资助项目 （）
