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Fast Method of Principal Component Analysis Based on L1-Norm Maximization Algorithm

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/39687

Title: Fast Method of Principal Component Analysis Based on L1-Norm Maximization Algorithm
Authors: Funatsu, Nobuhiro Browse this author
Kuroki, Yoshimitsu Browse this author
Issue Date: 4-Oct-2009
Publisher: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee
Journal Title: Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
Start Page: 262
End Page: 265
Abstract: In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2-PCA) is one of the most popular methods, but L2-PCA is sensitive to outliers. Unlike L2-PCA, PCA-L1 is robust to outliers because it utilizes the L1-norm, which is less sensitive to outliers. Furthermore, the bases obtained by PCA-L1 is invariant to rotations. However, PCA-L1 needs long time to calculate bases, because PCA-L1 employs an iterative algorithm to obtain each basis, and requires to calculate an eigenvector of autocorrelation matrix as an initial vector. The autocorrelation matrix needs to be recalculated for each basis. In this paper, we propose a fast method to compute the autocorrelation matrices. In order to verify the proposed method, we apply L2-PCA, PCA-L1, and the proposed method to face recognition. Simulation results show that the proposed method provides same recognition performance as PCA-L1, and is superior to L2-PCA, while the execution time is less than PCA-L1.
Description: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Poster session: Image, Video, and Multimedia Signal Processing 1 (5 October 2009).
Conference Name: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議
Conference Place: Sapporo
Type: proceedings
URI: http://hdl.handle.net/2115/39687
Appears in Collections:北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 2009) > 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)

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