Iterative subspace analysis based on feature line distance

Yanwei Pang, Yuan Yuan, Xuelong Li

科研成果: 期刊稿件文章同行评审

52 引用 (Scopus)

摘要

Nearest feature line-based subspace analysis is first proposed in this paper. Compared with conventional methods, the newly proposed one brings better generalization performance and incremental analysis. The projection point and feature line distance are expressed as a function of a subspace, which is obtained by minimizing the mean square feature line distance. Moreover, by adopting stochastic approximation rule to minimize the objective function in a gradient manner, the new method can be performed in an incremental mode, which makes it working well upon future data. Experimental results on the FERET face database and the UCI satellite image database demonstrate the effectiveness.

源语言英语
页(从-至)903-907
页数5
期刊IEEE Transactions on Image Processing
18
4
DOI
出版状态已出版 - 2009
已对外发布

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