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. Proc. of International Conference on Image Processing , 178-182.
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Description/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.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | Organisation: IEEE Address: Chicago, Illinois, USA |
| Divisions: | Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 250435 |
| Date Deposited: | 01 Dec 1999 |
| Last Modified: | 02 Mar 2012 12:38 |
| Contributors: | Huang, P.S. (Author) Harris, C.J. (Author) Nixon, M.S. (Author) |
| Date: | October 1998 |
| Additional Information: | Organisation: IEEE Address: Chicago, Illinois, USA |
| Status: | Published |
| Further Information: | Google Scholar |
| ISI Citation Count: | 0 |
| URI: | http://eprints.soton.ac.uk/id/eprint/250435 |
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