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基于压缩感知的人脸识别方法 被引量：6

Face Recognition Method Based on Compressed Sensing
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摘要 基于稀疏重构的分类方法具有较好的识别效果,但计算复杂度高。为此,提出基于压缩感知的人脸识别方法 COMP,将L1范数最小化重构算法替换成正交匹配追踪(OMP)算法,以降低复杂度,并在OMP中引入模式类别信息,使该方法具有更强的分类能力。基于YaleB人脸库的实验结果表明,COMP在低维度时识别率高于OMP。 Sparse Representation-based Classification（SRC） method performs excellent in face recognition but shows high complexity in computation.This paper proposes face recognition method based on Compressed Sensing（CS） named Classified Orthogonal Matching Pursuit（COMP）.L1-norm minimization representation algorithm is replaced by Orthogonal Matching Pursuit（OMP） algorithm to reduce complexity,and mode category information is introduced in OMP to endow the method stronger ability to category.Experiments based on YaleB face database clarify that the recognition rate of COMP is higher than OMP.
作者 邹伟 李元祥 杨俊杰 周则明
机构地区 上海交通大学航空航天学院 解放军理工大学气象学院
出处 《计算机工程》 CAS CSCD 2012年第24期133-136,共4页 Computer Engineering
基金 国家自然科学基金资助项目(41174164)
关键词 基于稀疏重构的分类方法 稀疏重构 L1范数最小化 正交匹配追踪算法 COMP方法 Sparse Representation-based Classification（SRC） method sparse representation L1-norm minimization Orthogonal Matching Pursuit（OMP） algorithm Classified Orthogonal Matching Pursuit（COMP） method
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献24

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二级参考文献127

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共引文献831

同被引文献72

  • 1蔡骋,张明,朱俊平.基于压缩感知理论的杂草种子分类识别[J].中国科学：信息科学,2010,40(S1):160-172. 被引量：17
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引证文献6

二级引证文献17

计算机工程
2012年 第24期

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