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Enhanced Human Identity and Gender Recognition from Gait Sequences using SVM and MDA

by Alka Saini, Harpreet Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 2
Year of Publication: 2015
Authors: Alka Saini, Harpreet Singh
10.5120/21037-3358

Alka Saini, Harpreet Singh . Enhanced Human Identity and Gender Recognition from Gait Sequences using SVM and MDA. International Journal of Computer Applications. 119, 2 ( June 2015), 6-9. DOI=10.5120/21037-3358

@article{ 10.5120/21037-3358,
author = { Alka Saini, Harpreet Singh },
title = { Enhanced Human Identity and Gender Recognition from Gait Sequences using SVM and MDA },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 2 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number2/21037-3358/ },
doi = { 10.5120/21037-3358 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:02:56.184670+05:30
%A Alka Saini
%A Harpreet Singh
%T Enhanced Human Identity and Gender Recognition from Gait Sequences using SVM and MDA
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 2
%P 6-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The identification through biometric is a better way because it associate with individual not with information passing from one place to another. There are numerous biometric measures which can be used to help derive an individual identity. It is the biometric process and has many advantages over other biometric traits such as face, iris, fingerprint, palm print, etc. Most current approaches make the unrealistic assumption that persons walk along a fixed direction or a pre-defined path. Gait is the manner or style of moving on foot. Human Gait recognition identifies the individuals by the way in which they walk. Recognition of an individual is an important task to identify people. A gait sequence is collected from arbitrary walking directions. In this paper we present the approach of human identity and gender recognition using Model based features extraction and SURF for matching along with SVM and MDA algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Gait recognition biometrics arbitrary direction SVM MDA.

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