Presentation 2015-05-15
Second-Order Tensor Principal Component Analysis Meets Two-Dimensional Singular Value Decomposition
Hayato Itoh, Atsushi Imiya, Tomoya Sakai,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) We show that the second-order tensor principal component analysis is theoretically equivalent to the two-dimensional singular value decomposition. For the practical computation of the two-dimensional singular value decomposition, we introduce the marginal eigenvector method. Furthermore, we show the relation among the two-dimensional singular value decomposition, the classical principal component analysis and the two-dimensional discrete cosine transform. For the comparison of performances of the marginal eigenvector and the two-dimensional discretecosine transform for dimension reduction, we compute recognition rates for face images. In this comparison, the marginal eigenvector method and the two-dimensional discrete cosine transform establish almost same performances to recognition rates.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) tensor principal component analysis / principal component analysis / singular value decomposition / marginal eigenvector / two-dimensional discrete cosine transform
Paper # SIP2015-14,IE2015-14,PRMU2015-14,MI2015-14
Date of Issue 2015-05-07 (SIP, IE, PRMU, MI)

Conference Information
Committee PRMU / MI / IE / SIP
Conference Date 2015/5/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Kazuhiko Sumi(Aoyama Gakuin Univ.) / Akinobu Shimizu(Tokyo Univ. of Agric. and Tech.) / Toshiaki Fujii(Nagoya Univ.) / Yoshinobu Kajikawa(Kansai Univ.)
Vice Chair Koichi Kise(Osaka Pref. Univ.) / Shuji Senda(NEC) / Yoshitaka Masutani(Hiroshima City Univ.) / Kensaku Mori(Nagoya Univ.) / Seishi Takamura(NTT) / Takayuki Hamamoto(Tokyo Univ. of Science) / Osamu Houshuyama(NEC) / Makoto Nakashizuka(Chiba Inst. of Tech.)
Secretary Koichi Kise(Kyushu Univ.) / Shuji Senda(Omron) / Yoshitaka Masutani(Tokushima Univ.) / Kensaku Mori(Kinki Univ.) / Seishi Takamura(NHK) / Takayuki Hamamoto(KDDI R&D Labs.) / Osamu Houshuyama(Ritsumeikan Univ.) / Makoto Nakashizuka(NEC)
Assistant Wataru Ohyama(Mie Univ.) / Mitsuru Anbai(DENSO IT Lab.) / Takayuki Kitasaka(Aichi Inst. of Tech.) / Hidetaka Hontani(Nagoya Inst. of Tech.) / Shohei Matsuo(NTT) / Takamichi Miyata(Chiba Inst. of Tech.) / Takamichi Miyata(Chiba Inst. of Tech.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Medical Imaging / Technical Committee on Image Engineering / Technical Committee on Signal Processing
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Second-Order Tensor Principal Component Analysis Meets Two-Dimensional Singular Value Decomposition
Sub Title (in English)
Keyword(1) tensor principal component analysis
Keyword(2) principal component analysis
Keyword(3) singular value decomposition
Keyword(4) marginal eigenvector
Keyword(5) two-dimensional discrete cosine transform
1st Author's Name Hayato Itoh
1st Author's Affiliation Chiba University(Chiba Univ.)
2nd Author's Name Atsushi Imiya
2nd Author's Affiliation Chiba University(Chiba Univ.)
3rd Author's Name Tomoya Sakai
3rd Author's Affiliation Chiba University(Chiba Univ.)
Date 2015-05-15
Paper # SIP2015-14,IE2015-14,PRMU2015-14,MI2015-14
Volume (vol) vol.115
Number (no) SIP-22,IE-23,PRMU-24,MI-25
Page pp.pp.71-75(SIP), pp.71-75(IE), pp.71-75(PRMU), pp.71-75(MI),
#Pages 5
Date of Issue 2015-05-07 (SIP, IE, PRMU, MI)