A unified view of two-dimensional principal component analyses

Kohei Inoue; Kenji Hara; Kiichi Urahama

doi:10.1007/978-3-642-34166-3_62

A unified view of two-dimensional principal component analyses

Kohei Inoue, Kenji Hara, Kiichi Urahama

Visual Communication Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recently, two-dimensional principal component analysis (2D-PCA) and its variants have been proposed by several researchers. In this paper, we summarize their 2DPCA variants, show some equivalence among them, and present a unified view in which the non-iterative 2DPCA variants are interpreted as the non-iterative approximate algorithms for the iterative 2DPCA variants, i.e., the non-iterative 2DPCA variants are derived as the first iterations of the iterative algorithm started from different initial settings. Then we classify the non-iterative 2DPCA variants on the basis of their algorithmic patterns and propose a new non-iterative 2DPCA algorithm based on the classification. The effectiveness of the proposed algorithm is experimentally demonstrated on three publicly accessible face image databases.

Original language	English
Title of host publication	Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings
Pages	566-574
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-34166-3_62
Publication status	Published - 2012
Event	Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012 - Hiroshima, Japan Duration: Nov 7 2012 → Nov 9 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7626 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012
Country	Japan
City	Hiroshima
Period	11/7/12 → 11/9/12

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-34166-3_62

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Inoue, K., Hara, K., & Urahama, K. (2012). A unified view of two-dimensional principal component analyses. In Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings (pp. 566-574). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7626 LNCS). https://doi.org/10.1007/978-3-642-34166-3_62

A unified view of two-dimensional principal component analyses. / Inoue, Kohei ; Hara, Kenji; Urahama, Kiichi.

Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings. 2012. p. 566-574 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7626 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Inoue, K , Hara, K & Urahama, K 2012, A unified view of two-dimensional principal component analyses. in Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7626 LNCS, pp. 566-574, Joint IAPR International Workshops on Structural and Syntactic PatternRecognition, SSPR 2012 and Statistical Techniques in Pattern Recognition,SPR 2012, Hiroshima, Japan, 11/7/12. https://doi.org/10.1007/978-3-642-34166-3_62

Inoue K , Hara K, Urahama K. A unified view of two-dimensional principal component analyses. In Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings. 2012. p. 566-574. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-34166-3_62

Inoue, Kohei ; Hara, Kenji ; Urahama, Kiichi. / A unified view of two-dimensional principal component analyses. Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2012, Proceedings. 2012. pp. 566-574 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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