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VisualSurveillance and Tracking of Humans by Face and Gait Recognition

Huang, P.S., Harris, C.J. and Nixon, M.S. (1998) VisualSurveillance and Tracking of Humans by Face and Gait Recognition At Proc. of 7th IFAC Symposium on Artificial Intelligence in Real-Time Control. , pp. 43-44.

Record type: Conference or Workshop Item (Other)

Abstract

Increased emphasis on automated real time intelligent surveillance system has led to the need to identify and track people in complex environments. Independent features such as face, gait provide valuable clues as to identity, which coupled with data fusion and tracking algorithms offer a potential solution to this problem. In this paper we address the first problem of recognizing humans in real time, data fusion and tracking will be performed by neurofuzzy state estimators. A new approach which combines eigenspace transformation with canonical space transformation is proposed here. This method can be used to reduce data dimensionality and to optimize the class separability of different classes simultaneously.

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More information

Published date: October 1998
Additional Information: Extended Version on CD Organisation: IFAC Address: Grand Canyon National Park, Arizona, USA
Venue - Dates: Proc. of 7th IFAC Symposium on Artificial Intelligence in Real-Time Control, 1998-10-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250438
URI: http://eprints.soton.ac.uk/id/eprint/250438
PURE UUID: 1a9dd03f-4a4a-465b-bb63-7c3a93a3f941

Catalogue record

Date deposited: 01 Dec 1999
Last modified: 18 Jul 2017 10:41

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Contributors

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

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