Identity and variation spaces: Revisiting the fisher linear discriminant

Sheng Zhang*, Terence Sim, Mei Chen Yeh

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

The Fisher Linear Discriminant (FLD) is commonly used in classification to find a subspace that maximally separates class patterns according to the Fisher Criterion. It was previously proven that a pre-whitening step can be used to truly optimize the Fisher Criterion. In this paper, we study the theoretical properties of the subspaces induced by this whitened FLD. Of the four subspaces induced, two are most important for classification and representation of patterns. We call these Identity Space and Variation Space. We show that only the between-class variation remains in Identity Space, and only the within-class variation remains in Variation Space. Both spaces can be used for decomposition and representation of class data. Moreover, we give sufficient conditions for these spaces to exist. Finally, we also run experiments to show how Identity and Variation Spaces may be used for classification and image synthesis.

原文英語
主出版物標題2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
頁面123-130
頁數8
DOIs
出版狀態已發佈 - 2009
事件2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, 日本
持續時間: 2009 九月 272009 十月 4

出版系列

名字2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

其他

其他2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
國家/地區日本
城市Kyoto
期間2009/09/272009/10/04

ASJC Scopus subject areas

  • 電腦視覺和模式識別
  • 電氣與電子工程

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