计算机工程与应用2016，Vol.52Issue(1)：219-223,5.DOI:10.3778/j.issn.1002-8331.1312-0318
基于子空间追踪的人脸识别
Face recognition based on subspace pursuit
摘要
Abstract
Against the disadvantage of haven't update selected atoms in existing face recognition method based on sparse representation, this paper proposes a face recognition based on subspace pursuit. This algorithm introduces back iterative optimization method and polyatomic options in the atomic choice in sparse coding, by removing the candidate atoms with low credibility to make sure that the chosen atoms have the most similar structure with the identifying face image, so the sparse coding coefficient can reconstruct faces well. The experimental results show that this algorithm has lower algorithm complexity and boosts about 5% recognition rate on ORL and Yale B face database compared with Orthogonal Matching Pursuit algorithm(OMP)and the OMP-cholesky algorithm.关键词
稀疏编码/稀疏表示/人脸识别/正交匹配追踪/子空间追踪Key words
sparse coding/sparse representation/face recognition/Orthogonal Matching Pursuit(OMP)/subspace pursuit分类
信息技术与安全科学引用本文复制引用
何双双,熊兵,张建明,吴宏林..基于子空间追踪的人脸识别[J].计算机工程与应用,2016,52(1):219-223,5.基金项目
国家自然科学基金青年项目(No.61202439) （No.61202439）
湖南省教育厅优秀青年项目(No.12B003) （No.12B003）
湖南省教育厅一般项目(No.12C0011) （No.12C0011）
湖南省交通运输厅科技进步与创新项目(No.201334). （No.201334）
