Visual Information and Camera Motion Fusion for 3D Target Tracking

Zhen, J; Balasuriya, A; Challa, S

Visual Information and Camera Motion Fusion for 3D Target Tracking

Zhen, J Balasuriya, A Challa, S

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Publisher:: ICARCV
Publication Type:: Conference Proceeding
Citation:: Proceedings of the Eighth International Conference on Control, Automation, Robotics and Vision, ICARCV 2004, 2004, pp. 2296 - 2301
Issue Date:: 2004-01

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Field	Value	Language
dc.contributor.author	Zhen, J	en_US
dc.contributor.author	Balasuriya, A	en_US
dc.contributor.author	Challa, S	en_US
dc.contributor.editor	No editors	en_US
dc.date	2004-12-06	en_US
dc.date.issued	2004-01	en_US
dc.identifier.citation	Proceedings of the Eighth International Conference on Control, Automation, Robotics and Vision, ICARCV 2004, 2004, pp. 2296 - 2301	en_US
dc.identifier.isbn	0-7803-8654-X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/7165
dc.description.abstract	This paper proposes a data fusion scheme for visual object identification and tracking by autonomous vehicles. In this scheme, image motion vectors fields, color features, visual disparity depth information and camera motion parameters are fused together to identify the target 3D visual and dynamic features. This paper also presents a detailed description of the 3D target tracking algorithm using an extended Kalman filter with a constant velocity dynamic model. Performance of the proposed scheme is discussed through experimental results.	en_US
dc.publisher	ICARCV	en_US
dc.relation.ispartof	Proceedings of the Eighth International Conference on Control, Automation, Robotics and Vision, ICARCV 2004	en_US
dc.relation.ispartof	International Conference on Control, Automation, Robotics and Vision	en_US
dc.relation.isbasedon	10.1109/ICARCV.2004.1469790	en_US
dc.title	Visual Information and Camera Motion Fusion for 3D Target Tracking	en_US
dc.type	Conference Proceeding
utslib.location	Kunming, China	en_US
utslib.location.activity	China	en_US
utslib.for	0909 Geomatic Engineering	en_US
dc.location.activity	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 Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	Kunming, China	en_US
pubs.start-date	2004-12-06	en_US

Abstract:

This paper proposes a data fusion scheme for visual object identification and tracking by autonomous vehicles. In this scheme, image motion vectors fields, color features, visual disparity depth information and camera motion parameters are fused together to identify the target 3D visual and dynamic features. This paper also presents a detailed description of the 3D target tracking algorithm using an extended Kalman filter with a constant velocity dynamic model. Performance of the proposed scheme is discussed through experimental results.

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

http://hdl.handle.net/10453/7165