We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

An Approach Defining Gait Recognition System using K-Means and MDA

by Riant Kaur, Heena
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 17
Year of Publication: 2015
Authors: Riant Kaur, Heena
10.5120/20643-3350

Riant Kaur, Heena . An Approach Defining Gait Recognition System using K-Means and MDA. International Journal of Computer Applications. 117, 17 ( May 2015), 1-4. DOI=10.5120/20643-3350

@article{ 10.5120/20643-3350,
author = { Riant Kaur, Heena },
title = { An Approach Defining Gait Recognition System using K-Means and MDA },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 17 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number17/20643-3350/ },
doi = { 10.5120/20643-3350 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:36.522170+05:30
%A Riant Kaur
%A Heena
%T An Approach Defining Gait Recognition System using K-Means and MDA
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 17
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biometric Authentication is a technology of verifying and identifying individuals. Gait Recognition is a type of biometric identification method which is related to behavioral characteristic of a person. Gait identifies a person based on the manner he moves or walks on foot. Gait needs reduced detail and is difficult to conceal Gait can identify people from a distance without their cooperation. Gait can be used in real time environments to detect threats and frauds. Gait can be captured using moving video, floor sensors or motion recording sensors. In the proposed work, firstly Gait is captured using moving video and binary silhouettes are generated. Secondly, feature extraction from each silhouette is done using GPPE. Lastly, recognition is performed using SVM, K-Means and MDA. Here, all the work will be performed on live input videos and gait MATLAB database.

References
  1. A. Hayder, J. Dargham, A. Chekima, and G. M. Ervin,"Person Identification Using Gait ", International Journal of Computer and Electrical Engineering, V. 3, No. 4,Aug 2011, pp. 477-482. Ding, W. and Marchionini, G. 1997 A Study on Video Browsing Strategies. Technical Report. University of Maryland at College Park.
  2. Arun Joshi, Shashi Bhushan, Jaspreet Kaur, "Gait Recognition of human using SVM and BPNN classifiers", International Journal of Computer Science and Mobile Computing, V. 3(1), 2014, pp. 281-290. Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.
  3. Hayder Ali, Jamal Dargham, Chekima Ali, Ervin Gobin Moung, "Gait Recognition using principle Component Analysis", Computer Engineering Program, School of Engineering and Information Technology, University Malaysia Sabah, Kota Kinabalu, The 3rd International Conference on Machine Vision, 2010, pp. 539-543.
  4. Ira Gaba, Paramjit Kaur, "Biometric Identification on The Basis of BPNN Classifier with Other Novel Techniques Used For Gait Analysis", International Journal of Recent Technology and Engineering, V. 2(4), 2013, pp. 137-142.
  5. Lili Liu, Yilong Yin, Wei Qin and Ying Li, "Gait Recognition Based on Outermost Contour", International Journal of Computational Intelligence Systems, V. 4, No. 5, Sep 2011, pp. 1090-1099.
  6. Liang Wang, Tieniu Tan, Huazhong Ning, and Weiming Hu, "Silhouette Analysis-Based Gait Recognition for Human Identification",IEEE Transactions on pattern analysis and machine intelligence, V. 25, No. 12, 2003, pp. 1505-1518.
  7. M. Jeevan, Neha Jain, M. Hanmandlu, GirijaChetty, "Gait Recognition Based On Gait Pal and Pal Entropy Image", IEEE, 2013, pp. 4195-4199.
  8. M. Pushpa Rani and G. Arumugam,"An Efficient Gait Recognition System for Human Identification using Modified ICA", International Journal of Computer Science and Information technology (IJCSIT) V. 2, No. 1, 2010, pp. 55-67.
  9. Parneet Kaur, Gurjot Kaur Walia, Amandeep Singh Dhaliwal, "Gait Recognition System for Improved Human Identification using ENN and NN", International journal of Advanced Research in Computer Science and Software Engineering, V. 3(11), Nov 2013, pp. 1154-1161.
  10. Qiong Cheng, Bo Fu, and Hui Chen, "Gait Recognition Based on PCA and LDA", Proceedings of the Second Symposium International Computer Science and Computational Technology (ISCSCT '09) Huangshan, P. R. China, 2009, pp. 124-127.
  11. Sagar A. More and Pramod J. Deore, "A Survey on Gait Biometrics", World Journal of Science and Technology, V. 2(4), 2012, pp. 146-151.
  12. Sanjeev Sharma, Ritu Tiwari, Anupamshukla and Vikas Singh, "Identification of People Using Gait Biometrics", International Journal of Machine Learning and Computing, V. 1,No. 4 2011, pp. 409-415
Index Terms

Computer Science
Information Sciences

Keywords

Gait Recognition System Gait Pal and Pal Entropy (GPPE) Support Vector Machine (SVM) K-Means Multi-linear Discriminant Analysis (MDA).