Presentation 2000/1/21
Object Recognition based on 2-D Orthogonal Expansion of Image
Takeshi Kobayashi, Shun'ichi Kaneko, Satoru Igarashi,
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Abstract(in English) We propose a new method to recognize 3-D object and its pose using approximate representation of image based on 2-D orthogonal expansion by marginal eigenvecters of column- and row-correlation matrices. The proposed method considers 2-D construction of image, and executes learning process by treating low dimensional matrices, so can learn any number of images with small computation cost compared with the method based on the K-L expansion. The method can also recognize any pose of an object, which is not learned, using smooth interpolation between highly correlated discrete images obtained in learning stage of the object. In this paper, we formulate the procedure and show effectiveness of the method through fundamental experiment.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) object reognition / pose estimation / eigenspace method / orthogonal expansion / marginal eigenvector
Paper # PRMU99-215
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Conference Information
Committee PRMU
Conference Date 2000/1/21(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Object Recognition based on 2-D Orthogonal Expansion of Image
Sub Title (in English)
Keyword(1) object reognition
Keyword(2) pose estimation
Keyword(3) eigenspace method
Keyword(4) orthogonal expansion
Keyword(5) marginal eigenvector
1st Author's Name Takeshi Kobayashi
1st Author's Affiliation Graduate School of Engineering, Hokkaido University()
2nd Author's Name Shun'ichi Kaneko
2nd Author's Affiliation Graduate School of Engineering, Hokkaido University
3rd Author's Name Satoru Igarashi
3rd Author's Affiliation Graduate School of Engineering, Hokkaido University
Date 2000/1/21
Paper # PRMU99-215
Volume (vol) vol.99
Number (no) 575
Page pp.pp.-
#Pages 6
Date of Issue