The University of Southampton
University of Southampton Institutional Repository

Automatic extraction and description of human gait models for recognition purposes

Cunado, David, Nixon, Mark S. and Carter, John N. (2003) Automatic extraction and description of human gait models for recognition purposes Computer Vision and Image Understanding, 90, (1), pp. 1-41. (doi:10.1016/S1077-3142(03)00008-0).

Record type: Article

Abstract

Using gait as a biometric is of emerging interest. We describe a new model-based moving feature extraction analysis is presented that automatically extracts and describes human gait for recognition. The gait signature is extracted directly from the evidence gathering process. This is possible by using a Fourier series to describe the motion of the upper leg and apply temporal evidence gathering techniques to extract the moving model from a sequence of images. Simulation results highlight potential performance benefits in the presence of noise. Classification uses the k-nearest neighbour rule applied to the Fourier components of the motion of the upper leg. Experimental analysis demonstrates that an improved classification rate is given by the phase-weighted Fourier magnitude information over the use of the magnitude information alone. The improved classification capability of the phase-weighted magnitude information is verified using statistical analysis of the separation of clusters in the feature space. Furthermore, the technique is shown to be able to handle high levels of occlusion, which is of especial importance in gait as the human body is self-occluding. As such, a new technique has been developed to automatically extract and describe a moving articulated shape, the human leg, and shown its potential in gait as a biometric.

PDF cunado_cviu.pdf - Version of Record
Download (720kB)

More information

Published date: April 2003

Identifiers

Local EPrints ID: 38715
URI: http://eprints.soton.ac.uk/id/eprint/38715
PURE UUID: 1d1f9c48-464f-4d2e-aefb-fbaf6b174e68

Catalogue record

Date deposited: 15 Jun 2006
Last modified: 17 Jul 2017 15:38

Export record

Altmetrics

Contributors

Author: David Cunado
Author: Mark S. Nixon
Author: John N. Carter

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×