A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates
A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates
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.
178-182
Huang, P.S.
a46d0155-1e6b-4874-ae22-b199c22d2f28
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
October 1998
Huang, P.S.
a46d0155-1e6b-4874-ae22-b199c22d2f28
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Huang, P.S., Harris, C.J. and Nixon, M.S.
(1998)
A Statistical Approach for Recognizing Humans by Gait using Spatial-Temporal Templates.
Proc. of International Conference on Image Processing.
.
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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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Published date: October 1998
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Organisation: IEEE Address: Chicago, Illinois, USA
Venue - Dates:
Proc. of International Conference on Image Processing, 1998-09-30
Organisations:
Southampton Wireless Group
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Local EPrints ID: 250435
URI: http://eprints.soton.ac.uk/id/eprint/250435
PURE UUID: e6596fbd-c2fa-4082-8b6a-869d9a46e9dc
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Date deposited: 01 Dec 1999
Last modified: 09 Jan 2022 02:33
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Contributors
Author:
P.S. Huang
Author:
C.J. Harris
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