Gait-based person identification robust to changes in appearance

Yumi Iwashita, Koji Uchino, Ryo Kurazume

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)7884-7901
Number of pages18
JournalSensors (Switzerland)
Volume13
Issue number6
DOIs
Publication statusPublished - Jun 2013

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Gait-based person identification robust to changes in appearance'. Together they form a unique fingerprint.

Cite this