A new automatic gait cycle partitioning method and its application to human identification

Sungjun Hong, Euntai Kim

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Gait cycle partitioning is very important prior to human gait analysis such as gait modeling, gait recognition, gait feature analysis, etc. In this paper, we propose a new automatic gait cycle partitioning method based on two kinds of simple gait representation. Then, the propose method is applied to find keyframe corresponding the rest position for gait-based human identification system. To demonstrate the validity of the proposed method, the CASIA gait dataset A and the SOTON gait database are used to evaluate the recognition performance of the gait recognition system identifying subjects using the decision level fusion based on majority voting.

Original languageEnglish
Pages (from-to)51-57
Number of pages7
JournalInternational Journal of Fuzzy Logic and Intelligent Systems
Issue number2
Publication statusPublished - 2017

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) through the Biometrics Engineering Research Center (BERC) at Yonsei University in 2010 (Grant No. R11-2002-105-09002-0).

Publisher Copyright:
© The Korean Institute of Intelligent Systems.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Logic
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Artificial Intelligence


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