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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)

Abstract

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.

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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

Identifiers

Local EPrints ID: 250435
URI: http://eprints.soton.ac.uk/id/eprint/250435
PURE UUID: e6596fbd-c2fa-4082-8b6a-869d9a46e9dc

Catalogue record

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

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Contributors

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

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