Abstract
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 language | English |
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Pages (from-to) | 51-57 |
Number of pages | 7 |
Journal | International Journal of Fuzzy Logic and Intelligent Systems |
Volume | 17 |
Issue number | 2 |
DOIs | |
Publication status | Published - 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