The University of Southampton
University of Southampton Institutional Repository

Model-based Gait Recognition

Model-based Gait Recognition
Model-based Gait Recognition
Model-based Gait Recognition concerns identification using an underlying mathematical construct(s) representing the discriminatory gait characteristics (be they static or dynamic), with a set of parameters and a set of logical and quantitative relationships between them. These models are often simplified based on justifiable assumptions such as the system only accounts for pathologically normal gait. Such a system normally consists of gait capture, a model(s), a feature extraction scheme, a gait signature and a classifier (Figure 1). The model can be a 2- or 3-dimensional structural (or shape) model and motion model that lays the foundation for the extraction and tracking of a moving person. An alternative to a model-based approach is to analyse the motion of the human silhouette deriving recognition from the body’s shape and motion. A gait signature that is unique to each person in the database is then derived from the extracted gait characteristics. In the classification stage, many pattern classification techniques can be used, such as the k-nearest neighbour approach.
633-639
Springer
yam, cy
21660f75-16bd-48e9-b4df-4788e9418ac7
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
yam, cy
21660f75-16bd-48e9-b4df-4788e9418ac7
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

yam, cy and Nixon, Mark (2009) Model-based Gait Recognition. In, Enclycopedia of Biometrics. Springer, pp. 633-639.

Record type: Book Section

Abstract

Model-based Gait Recognition concerns identification using an underlying mathematical construct(s) representing the discriminatory gait characteristics (be they static or dynamic), with a set of parameters and a set of logical and quantitative relationships between them. These models are often simplified based on justifiable assumptions such as the system only accounts for pathologically normal gait. Such a system normally consists of gait capture, a model(s), a feature extraction scheme, a gait signature and a classifier (Figure 1). The model can be a 2- or 3-dimensional structural (or shape) model and motion model that lays the foundation for the extraction and tracking of a moving person. An alternative to a model-based approach is to analyse the motion of the human silhouette deriving recognition from the body’s shape and motion. A gait signature that is unique to each person in the database is then derived from the extracted gait characteristics. In the classification stage, many pattern classification techniques can be used, such as the k-nearest neighbour approach.

Text
Model-based_Gait_Recognition_final.pdf - Other
Download (490kB)

More information

Published date: 2009
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 268238
URI: https://eprints.soton.ac.uk/id/eprint/268238
PURE UUID: d6fbb75b-048d-45aa-b554-8ea95ab8afe6
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 19 Nov 2009 16:21
Last modified: 20 Jul 2019 01:28

Export record

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 https://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.

×