Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)

Research on Gait Recognition Method Based on Gait Frame Difference Entropy Image

Authors
Zhanli Li, Fang Yang, Jingding Fu
Corresponding Author
Zhanli Li
Available Online September 2016.
DOI
10.2991/icence-16.2016.88How to use a DOI?
Keywords
GFDEI, GFDEnI, Shannon entropy, KNN
Abstract

To the relatively low recognition rate of gait frame difference energy image (GFDEI), this paper proposes gait frame difference entropy image (GFDEnI) to describe gait feature based on it, and then adopts improved KNN to recognize. GFDEnI describes the uncertainty of each point using Shannon entropy theory, and makes the description more accurate. Experimental results show that the algorithm this paper proposes obtains better recognition effect under the three states of ordinary condition, coat wearing and bag wearing, and has certain robustness to human clothing change.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
10.2991/icence-16.2016.88
ISSN
2352-538X
DOI
10.2991/icence-16.2016.88How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhanli Li
AU  - Fang Yang
AU  - Jingding Fu
PY  - 2016/09
DA  - 2016/09
TI  - Research on Gait Recognition Method Based on Gait Frame Difference Entropy Image
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 465
EP  - 470
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.88
DO  - 10.2991/icence-16.2016.88
ID  - Li2016/09
ER  -