Presentation 1998/5/21
Eigenspace Approach for Object Recognition and its Pose Detection.
Toshiyuki AMANO, Akashi YAMAGUCHI, Seiji INOKUCHI,
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Abstract(in English) Range-image is one of a useful data for the recognition and localization of freeform 3-D object. Most recognition and pose-detection methods from range-image have to use a feature extraction, but it is necessary a simply model and difficult to extract features. Besides central to this issue is the problem of feature matching on the object and range-image. So we proposed use of appearance-matching technique on the range-image. To use range image for the appearance-matching has one more advantage. Range-image expresses a geometrical object information. So, it is easy to make range-image from polygon data to using camera-parameter, and large numbers of sample images from reality measurement are not necessary. In the fact large number of sample is the key to use appearance-matching. In this paper we propose a methodology for the recognition and pose-detection of freeform 3-D object by appearance-matching on the range-image.
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Keyword(in English) Range-image / Eigenspace-representayion / Virtual-learning / Pixel-lack
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Conference Information
Committee PRMU
Conference Date 1998/5/21(1days)
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Paper Information
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) Eigenspace Approach for Object Recognition and its Pose Detection.
Sub Title (in English)
Keyword(1) Range-image
Keyword(2) Eigenspace-representayion
Keyword(3) Virtual-learning
Keyword(4) Pixel-lack
1st Author's Name Toshiyuki AMANO
1st Author's Affiliation Graduate School of Engineering Science, Osaka University()
2nd Author's Name Akashi YAMAGUCHI
2nd Author's Affiliation Graduate School of Engineering Science, Osaka University
3rd Author's Name Seiji INOKUCHI
3rd Author's Affiliation Graduate School of Engineering Science, Osaka University
Date 1998/5/21
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Volume (vol) vol.98
Number (no) 69
Page pp.pp.-
#Pages 8
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