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/).
Cite this article
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 -