西华大学学报（自然科学版）Issue(1)：60-64,5.DOI:10.3969/j.issn.1673-159X.2014.01.015
零空间边界 Fisher 分析法及其在人脸识别中的应用
Null Space Marginal Fisher Analysis and Its Application in Face Recognition
杨军 1刘妍丽2
作者信息
- 1. 四川师范大学计算机科学学院，四川 成都 610101
- 2. 四川师范大学数学与软件学院，四川 成都 610101
- 折叠
摘要
Abstract
Marginal Fisher analysis ( MFA) is an efficient linear projection technique for feature extraction .The major drawback of applying MFA to face recognition is that it often encounters the small sample size ( SSS) problem.In this paper, a strategy based on null space for solving optimization criteria of MFA is proposed to avoid this issue .It maximizes the class scatter of training samples on null space of within-class scatter matrix ( Sw ) in MFA and reserves the discriminant information contained in null space of Sw .The per-formance of this method is tested in both ORL and Yale face databases .Experimental results show that this method is effective and a-chieves higher recognition rate than LDA and MFA .Moreover , it is easy to decide most optimal dimensionality of feature space for this method .关键词
人脸识别/边界Fisher分析/小样本问题/零空间Key words
face recognition/marginal fisher analysis ( MFA)/small sample size ( SSS) problem/null space分类
信息技术与安全科学引用本文复制引用
杨军,刘妍丽..零空间边界 Fisher 分析法及其在人脸识别中的应用[J].西华大学学报（自然科学版）,2014,(1):60-64,5.
