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.
|Number of pages||7|
|Journal||International Journal of Fuzzy Logic and Intelligent Systems|
|Publication status||Published - 2017|
Bibliographical noteFunding 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).
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Science Applications
- Computational Theory and Mathematics
- Artificial Intelligence