Journal of Robotics, Networking and Artificial Life

Volume 1, Issue 3, December 2014, Pages 194 - 197

Human Recognition based on Gait Features and Genetic Programming

Authors
Dipak Gaire Sharma, Rahadian Yusuf, Ivan Tanev, Katsunori Shimohara
Corresponding Author
Dipak Gaire Sharma
Available Online 15 December 2014.
DOI
https://doi.org/10.2991/jrnal.2014.1.3.5How to use a DOI?
Keywords
Human Identification, Biometrics, Genetic Programming, Human Gaits, Nature Inspired Computing
Abstract

Human walking has always been the curious field of research for different disciple of social and information science. The study of human walk or human gait in association with different behaviors and emotions has not only fascinated social science researchers, but its uniqueness has also attracted many computer scientists to work in this arena for the quest of uncovering reliable mechanisms of biometric identification. In this research, we used a novel method for human identification based on inferring the relationship between the human gait features via genetic programming. Moreover, we focus on generating the unique numerical signature that is similar for different locomotion gaits of a particular individual but different across different individuals.

Copyright
© 2013, 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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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
1 - 3
Pages
194 - 197
Publication Date
2014/12/15
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2014.1.3.5How to use a DOI?
Copyright
© 2013, 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  - JOUR
AU  - Dipak Gaire Sharma
AU  - Rahadian Yusuf
AU  - Ivan Tanev
AU  - Katsunori Shimohara
PY  - 2014
DA  - 2014/12/15
TI  - Human Recognition based on Gait Features and Genetic Programming
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 194
EP  - 197
VL  - 1
IS  - 3
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2014.1.3.5
DO  - https://doi.org/10.2991/jrnal.2014.1.3.5
ID  - Sharma2014
ER  -