A review of tracking methods under occlusions

Zhang, Z; Piccardi, M

A review of tracking methods under occlusions

Zhang, Z Piccardi, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings of IAPR Conference on Machine Vision Applications, MVA 2007, 2007, pp. 146 - 149
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Zhang, Z	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	Proceedings of IAPR Conference on Machine Vision Applications, MVA 2007, 2007, pp. 146 - 149	en_US
dc.identifier.isbn	9784901122078	en_US
dc.identifier.uri	http://hdl.handle.net/10453/6821
dc.description.abstract	Object tracking in computer vision refers to the task of tracking individual moving objects accurately from one frame to another in an image sequence. Several tracking methods have been proposed in the recent literature capable of coping with a certain degree of occlusions of the objects. However, no comparative analysis of such methods has been presented to date and both the expert and the newcomer to this area may be confused about the relative effectiveness of each method when compared under the same level of complexity of the dynamic scene. In order to fulfill this need, this paper proposes a set of analysis criteria and provides a comparative review of the main recent tracking methods, in particular with respect to their capability of tracking objects under occlusions.	en_US
dc.relation.ispartof	Proceedings of IAPR Conference on Machine Vision Applications, MVA 2007	en_US
dc.title	A review of tracking methods under occlusions	en_US
dc.type	Conference Proceeding
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Tokyo, Japan	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:

Object tracking in computer vision refers to the task of tracking individual moving objects accurately from one frame to another in an image sequence. Several tracking methods have been proposed in the recent literature capable of coping with a certain degree of occlusions of the objects. However, no comparative analysis of such methods has been presented to date and both the expert and the newcomer to this area may be confused about the relative effectiveness of each method when compared under the same level of complexity of the dynamic scene. In order to fulfill this need, this paper proposes a set of analysis criteria and provides a comparative review of the main recent tracking methods, in particular with respect to their capability of tracking objects under occlusions.

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http://hdl.handle.net/10453/6821