Gait-based person identification robust to changes in appearance

Yumi Iwashita, Koji Uchino, Ryo Kurazume

研究成果: ジャーナルへの寄稿学術誌査読

47 被引用数 (Scopus)

抄録

The identification of a person from gait images is generally sensitive to appearance changes, such as variations of clothes and belongings. One possibility to deal with this problem is to collect possible subjects' appearance changes in a database. However, it is almost impossible to predict all appearance changes in advance. In this paper, we propose a novel method, which allows robustly identifying people in spite of changes in appearance, without using a database of predicted appearance changes. In the proposed method, firstly, the human body image is divided into multiple areas, and features for each area are extracted. Next, a matching weight for each area is estimated based on the similarity between the extracted features and those in the database for standard clothes. Finally, the subject is identified by weighted integration of similarities in all areas. Experiments using the gait database CASIA show the best correct classification rate compared with conventional methods experiments.

本文言語英語
ページ(範囲)7884-7901
ページ数18
ジャーナルSensors (Switzerland)
13
6
DOI
出版ステータス出版済み - 6月 2013

!!!All Science Journal Classification (ASJC) codes

  • 分析化学
  • 生化学
  • 原子分子物理学および光学
  • 器械工学
  • 電子工学および電気工学

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