Gait Recognition Based-on Relative Motion Features and Kinect

Authors

Yang Ke, National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha 410073, China;
Dou Yong, National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha 410073, China;
Lv Shaohe, National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha 410073, China;

Abstract

Abstract: Gait recognition Kinect is a very important biometric technology. Gait feature can be divided into two categories: static and dynamic. Some work found that although the essential characteristics of gait are motion, but the motion feature's recognition capability is limited. However, is the distinguishing ability of the motion itself limited, or existing features doesn't adequately capture the characteristics of motion? Relative distance-based motion features were proposed, and distances between the particular skeleton points and their changes were used to characterize the gait. The relative motion features were extracted without calculating the gait cycle, and with robustness. Experimental results show that the relative motion features' recognition accuracy is up to 84%, which is equivalent to static characteristic.

Recommended Citation

Ke, Yang; Yong, Dou; and Shaohe, Lv (2020) "Gait Recognition Based-on Relative Motion Features and Kinect," Journal of System Simulation: Vol. 27: Iss. 10, Article 11.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/11

First Page

2299

Revised Date

2015-07-31

DOI Link

https://doi.org/

Last Page

2304

CLC

TP391.9

Recommended Citation

Yang Ke, Dou Yong, Lv Shaohe. Gait Recognition Based-on Relative Motion Features and Kinect[J]. Journal of System Simulation, 2015, 27(10): 2299-2304.