Semi-supervised intelligent surveillance system for secure environments

Fookes, C; Denman, S; Lakemond, R; Ryan, D; Sridharan, S; Piccardi, M

Semi-supervised intelligent surveillance system for secure environments

Fookes, C Denman, S Lakemond, R Ryan, D Sridharan, S Piccardi, M

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Publication Type:: Conference Proceeding
Citation:: IEEE International Symposium on Industrial Electronics, 2010, pp. 2815 - 2820
Issue Date:: 2010-12-27

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Field	Value	Language
dc.contributor.author	Fookes, C	en_US
dc.contributor.author	Denman, S	en_US
dc.contributor.author	Lakemond, R	en_US
dc.contributor.author	Ryan, D	en_US
dc.contributor.author	Sridharan, S	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2010-12-27	en_US
dc.identifier.citation	IEEE International Symposium on Industrial Electronics, 2010, pp. 2815 - 2820	en_US
dc.identifier.isbn	9781424463916	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16144
dc.description.abstract	This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted. © 2010 IEEE.	en_US
dc.relation.ispartof	IEEE International Symposium on Industrial Electronics	en_US
dc.relation.isbasedon	10.1109/ISIE.2010.5636922	en_US
dc.title	Semi-supervised intelligent surveillance system for secure environments	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Bari, Italy	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted. © 2010 IEEE.

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http://hdl.handle.net/10453/16144