The University of Southampton
University of Southampton Institutional Repository

A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates

Huang, P.S., Harris, C.J. and Nixon, M.S. (1998) A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates At Proc. of International Conference on Image Processing. , pp. 178-182.

Record type: Conference or Workshop Item (Other)


In order to tackle the problem of recognizing humans by gait, we use an approach which combines eigenspace transformation (EST) with canonical space transformation (CST) for feature extraction of spatial templates from a gait sequence. Our proposed method can be used to reduce data dimensionality and to optimize the class separability of different gait sequences simultaneously. In this paper, we propose a new feature - temporal templates , and an extended feature which combines spatial and temporal templates for recognition. By incorporating spatial and temporal information into an extended feature vector in the canonical space, gait recognition becomes more robust and accurate than using any single feature alone.

Full text not available from this repository.

More information

Published date: October 1998
Additional Information: Organisation: IEEE Address: Chicago, Illinois, USA
Venue - Dates: Proc. of International Conference on Image Processing, 1998-10-01
Organisations: Southampton Wireless Group


Local EPrints ID: 250435
PURE UUID: e6596fbd-c2fa-4082-8b6a-869d9a46e9dc

Catalogue record

Date deposited: 01 Dec 1999
Last modified: 18 Jul 2017 10:42

Export record


Author: P.S. Huang
Author: C.J. Harris
Author: M.S. Nixon

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 supports OAI 2.0 with a base URL of

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.