Presentation 2011-03-11
Person identification robust to changes in appearance
Yumi IWASHITA, Koji UCHINO, Ryo KURAZUME,
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Abstract(in English) This paper presents a novel method for gait-based person identification robust to changes in appearance. Gait is sensitive to appearance changes, such as variations of clothes and carrying conditions, so the correct classification rate is reduced in case target's appearance condition is different from that in the database. To deal with this problem, a part-based gait identification method has been proposed. In this method the human body is divided into eight parts, and the discrimination capability of each part, which is trained with training datasets including various types of clothes, is controlled to correspond to different changes of clothes. However, the correct classification rate would be reduced in case target's clothes are not included in the training datasets. So we propose a new part-based person identification method, where the discrimination capability at each part is directly controlled based on gait features between gallery datasets and probe dataset. Experiments using a gait database CASIA show the effectiveness of the proposed method.
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Keyword(in English) Gait / person identification / affine moment invariants / local features
Paper # PRMU2010-281
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Conference Information
Committee PRMU
Conference Date 2011/3/3(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) Person identification robust to changes in appearance
Sub Title (in English)
Keyword(1) Gait
Keyword(2) person identification
Keyword(3) affine moment invariants
Keyword(4) local features
1st Author's Name Yumi IWASHITA
1st Author's Affiliation Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name Koji UCHINO
2nd Author's Affiliation Electrical Engineering and Computer Science, Kyushu University
3rd Author's Name Ryo KURAZUME
3rd Author's Affiliation Information Science and Electrical Engineering, Kyushu University
Date 2011-03-11
Paper # PRMU2010-281
Volume (vol) vol.110
Number (no) 467
Page pp.pp.-
#Pages 5
Date of Issue