Presentation 2010-03-15
Person identification using mine moment invariants
Yumi IWASHITA, Ryo KURAZUME,
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Abstract(in English) Gait is one of biometrics which offer the possibility to identify people at a distance, without any inter action or cooperation from the subject, compared with other kind of biometrics, such as fingerprints and iris. To identify people by gait, gait features based on a model of the human body or one's appearance are extracted from captured image sequences of walking people. Various methods have been proposed so far, and a Fourier transform-based method enabled to identify people with high correct classification rate. However, the dimension number of features rises in parallel with the increasing of the image resolution. In this paper, we introduce a resolution independent method using affine moment invariants, which enables to identify people with high correct classification using small dimension number of features. We applied the proposed method to a gait database SOTON, and used the leaveone-out cross validation technique to estimate the correct classification rate of 98 % with twentieth part of dimension number of features of the conventional method.
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Keyword(in English) Gait / person identification / affine moment invariants
Paper # PRMU2009-246,HIP2009-131
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Committee HIP
Conference Date 2010/3/8(1days)
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Registration To Human Information Processing (HIP)
Language JPN
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Title (in English) Person identification using mine moment invariants
Sub Title (in English)
Keyword(1) Gait
Keyword(2) person identification
Keyword(3) affine moment invariants
1st Author's Name Yumi IWASHITA
1st Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name Ryo KURAZUME
2nd Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
Date 2010-03-15
Paper # PRMU2009-246,HIP2009-131
Volume (vol) vol.109
Number (no) 471
Page pp.pp.-
#Pages 6
Date of Issue