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Human Gait Recognition using Silhouette Vector and Principal Component Analysis

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IJCA Proceedings on National Conference on Advances in Communication and Computing
© 2014 by IJCA Journal
NCACC 2014 - Number 1
Year of Publication: 2014
Authors:
Sagar A. More
Pramod J. Deore

Sagar A More and Pramod J Deore. Article: Human Gait Recognition using Silhouette Vector and Principal Component Analysis. IJCA Proceedings on National Conference on Advances in Communication and Computing NCACC(1):1-6, December 2014. Full text available. BibTeX

@article{key:article,
	author = {Sagar A. More and Pramod J. Deore},
	title = {Article: Human Gait Recognition using Silhouette Vector and Principal Component Analysis},
	journal = {IJCA Proceedings on National Conference on Advances in Communication and Computing},
	year = {2014},
	volume = {NCACC},
	number = {1},
	pages = {1-6},
	month = {December},
	note = {Full text available}
}

Abstract

Lot of research in the field of human recognition is being carried out. Gait recognition is a relatively new approach which is gaining momentum in biometrics. We have demonstrated a simple approach as a solution to this problem. We have taken a feature which was proposed earlier i. e. the Silhouette Vector. This is the distance of boundary points from the centroid of the silhouette as it rotates 360 degrees. Additional to the silhouette vector, we divided the silhouette image into three equal parts vertically (Rectangular Features) and computed some statistical properties of these parts. These properties were also added to the silhouette vector and given to the PCA training system. Training was performed using silhouette vectors and rectangular vectors for each subject. For testing the system, nearest neighbor method was used which is one of the simplest algorithms used for classification problems. The test subject is assigned to the class which is the minimum Euclidean distance from it. Inclusion of the additional features has improved the system performance greatly. Cumulative match score was used to analyze the system performance.

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