Robust object tracking using the particle filtering and level set methods: A comparative experiment

Luo, C; Cai, X; Zhang, J

Robust object tracking using the particle filtering and level set methods: A comparative experiment

Luo, C Cai, X Zhang, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008, 2008, pp. 359 - 364
Issue Date:: 2008-12-31

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Field	Value	Language
dc.contributor.author	Luo, C	en_US
dc.contributor.author	Cai, X	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0002-7240-3541	en_US
dc.date.issued	2008-12-31	en_US
dc.identifier.citation	Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008, 2008, pp. 359 - 364	en_US
dc.identifier.isbn	9781424422951	en_US
dc.identifier.uri	http://hdl.handle.net/10453/29753
dc.description.abstract	Robust visual tracking has become an important topic of research in computer vision. A novel method for robust object tracking, GATE [11], improves object tracking in complex environments using the particle filtering and the level set-based active contour method. GATE creates a spatial prior in the state space using shape information of the tracked object to filter particles in the state space in order to reshape and refine the posterior distribution of the particle filtering. This paper describes a comparative experiment that applies GATE and the standard particle filtering to track the object of interest in complex environments using simple features. Image sequences captured by the hand held, stationary and the PTZ camera are utilised. The experimental results demonstrate that GATE is able to solve the ambiguous outlier problem of particle filters in order to deal with heavy clutters in the background, occlusion, low resolution and noisy images, and thus significantly improves the particle filtering in object tracking. © 2008 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008	en_US
dc.relation.isbasedon	10.1109/MMSP.2008.4665104	en_US
dc.title	Robust object tracking using the particle filtering and level set methods: A comparative experiment	en_US
dc.type	Conference Proceeding
utslib.for	1005 Communications Technologies	en_US
dc.location.activity	Cairns, QLD	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:

Robust visual tracking has become an important topic of research in computer vision. A novel method for robust object tracking, GATE [11], improves object tracking in complex environments using the particle filtering and the level set-based active contour method. GATE creates a spatial prior in the state space using shape information of the tracked object to filter particles in the state space in order to reshape and refine the posterior distribution of the particle filtering. This paper describes a comparative experiment that applies GATE and the standard particle filtering to track the object of interest in complex environments using simple features. Image sequences captured by the hand held, stationary and the PTZ camera are utilised. The experimental results demonstrate that GATE is able to solve the ambiguous outlier problem of particle filters in order to deal with heavy clutters in the background, occlusion, low resolution and noisy images, and thus significantly improves the particle filtering in object tracking. © 2008 IEEE.

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http://hdl.handle.net/10453/29753