[1]袁安鼎[],荆晓远[],吴飞[]. 基于局部信息融合的正交稀疏保留投影分析[J].计算机技术与发展,2017,27(01):61-64.
　YUAN An-ding[],JING Xiao-yuan[],WU Fei[]. Analysis of Orthogonal Sparse Preserving Projection Based on Local Information Fusion[J].,2017,27(01):61-64.
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 基于局部信息融合的正交稀疏保留投影分析()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年01期
页码:
61-64
栏目:
智能、算法、系统工程
出版日期:
2017-01-10

文章信息/Info

Title:
 Analysis of Orthogonal Sparse Preserving Projection Based on Local Information Fusion
文章编号:
1673-629X（2017)01-0061-04
作者:
 袁安鼎[1]; 荆晓远[1] ; 吴飞[2]
 1.南京邮电大学 自动化学院；2.南京邮电大学 通信与信息工程学院
Author(s):
 YUAN An-ding[1]; JING Xiao-yuan[1]; WU Fei[2]
关键词:
 ; 稀疏保留投影; 局部近邻信息; 正交性; 迭代终止准则
Keywords:
 ; sparsity preserving projections; local neighbor information; orthogonality; iterative stopping criterion
分类号:
TP301
文献标志码:
A
摘要:
 模式识别领域对于样本分类判别的准则有很多，近期运用比较多的是将原始数据样本的稀疏重构关系保持到投影变换后的样本空间中，从而增加分类的准确性。稀疏保留投影算法( SPP)就是基于该思想发展起来的典型算法。该算法在寻找最佳投影变换时是从样本的全局角度出发，没有考虑到样本总体呈现非线性而局部线性的空间结构，样本间的局部信息对识别率同样有很大的提升作用，同时SPP算法获取的投影变化是非正交的，特征变换之间存在冗余信息，特征信息之间存在冗余的情况对于样本分类过程存在很大的干扰项。基于以上不足之处，提出基于局部信息融合的正交稀疏保留投影，将正交性以及样本间的局部结构信息融入SPP算法之中，同时在AR以及CAS-PEAL人脸库上对所提算法进行验证。
Abstract:
 There are many sample classification criterion in the field of pattern recognition,and the mostly used one recently is to maintain the sparse reconstruction relationship of original data samples to the sample space after projection transformation so as to increase the ac-curacy of classification. SPP is a typical algorithm based on the idea. In finding the optimal projection transformation,SPP is based on the global point view,however the spatial structure of the sample is nonlinear and the local linear structure is not considered. At the same time,the SPP algorithm is not orthogonal,and there is redundant information between the feature transform. Based on the above shortcom-ings,orthogonal sparse preserving projection based on local information fusion is proposed,and the orthogonality and the local structure information of samples are merged into the SPP algorithm. At the same time,the proposed algorithm is validated on the AR and CAS-PEAL face database.

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更新日期/Last Update: 2017-04-01