A novel Approach to Human Gait Recognition using possible Speed Invariant features

DOI

10.1080/18756891.2014.967004How to use a DOI?

Keywords

Human Gait, Polygon area, Convex Hull, Bayes’ Decision rule, Mahalanobis Distance, Polynomial based distance metrics

Abstract

In this paper a new area based technique is proposed for deriving gait signatures by decomposing the human body into three independent structural segments such as head node, arm swing and leg swing areas. Initially, all the feature points are represented as the sides of an n-sided polygon for calculating the area of each region. This technique induces surplus noise in the feature points which is in turn reflected in the human identification problem. This drawback inspires us to compute the area of each region by constructing a convex hull of the feature points in order to obtain certain key speed invariant features. Classification results demonstrate the ability of proposed feature extraction techniques using Bayes’ classifier, distance metrics, and the proposed polynomial based distance metric. The performance analysis of various classifiers has been evaluated using Receiver Operating Characteristics (ROC) curve and the Cumulative Match Characteristics Curve (CMC) after performing N-fold cross validation technique.

Copyright

© 2017, 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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TY  - JOUR
AU  - Anup Nandy
AU  - Rupak Chakraborty
AU  - Pavan Chakraborty
AU  - G.C. Nandi
PY  - 2014
DA  - 2014/12/01
TI  - A novel Approach to Human Gait Recognition using possible Speed Invariant features
JO  - International Journal of Computational Intelligence Systems
SP  - 1174
EP  - 1193
VL  - 7
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2014.967004
DO  - 10.1080/18756891.2014.967004
ID  - Nandy2014
ER  -