Robust mean-shift tracking with extended fast colour thresholding

Xu, RYD; Allen, JG; Jin, JS

Robust mean-shift tracking with extended fast colour thresholding

Xu, RYD Allen, JG Jin, JS

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Publication Type:: Conference Proceeding
Citation:: 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2004, 2004, pp. 542 - 545
Issue Date:: 2004-12-01

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Field	Value	Language
dc.contributor.author	Xu, RYD	en_US
dc.contributor.author	Allen, JG	en_US
dc.contributor.author	Jin, JS	en_US
dc.date.issued	2004-12-01	en_US
dc.identifier.citation	2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2004, 2004, pp. 542 - 545	en_US
dc.identifier.isbn	0780386884	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2390
dc.description.abstract	We propose a novel adaptive approach for object tracking using fast colour thresholding and region merging. It proves to be an effective measure against large variations between consecutive frames during a mean-shift process. The approach retains mean-shift's property of efficiency and improves mean-shift's drawback of robustness. It can track non-rigid objects with significant occlusion.	en_US
dc.relation.ispartof	2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2004	en_US
dc.title	Robust mean-shift tracking with extended fast colour thresholding	en_US
dc.type	Conference Proceeding
utslib.for	1006 Computer Hardware	en_US
dc.location.activity	Hong Kong, China	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 Business
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
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

We propose a novel adaptive approach for object tracking using fast colour thresholding and region merging. It proves to be an effective measure against large variations between consecutive frames during a mean-shift process. The approach retains mean-shift's property of efficiency and improves mean-shift's drawback of robustness. It can track non-rigid objects with significant occlusion.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/2390