Eight solutions of the essential matrix for continuous camera motion tracking in video augmented reality

Ling, L; Cheng, E; Burnett, IS

Eight solutions of the essential matrix for continuous camera motion tracking in video augmented reality

Ling, L Cheng, E

Burnett, IS

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Publication Type:: Conference Proceeding
Citation:: Proceedings - IEEE International Conference on Multimedia and Expo, 2011
Issue Date:: 2011-11-07

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Field	Value	Language
dc.contributor.author	Ling, L	en_US
dc.contributor.author	Cheng, E https://orcid.org/0000-0003-1632-8062	en_US
dc.contributor.author	Burnett, IS https://orcid.org/0000-0003-3795-7722	en_US
dc.date.issued	2011-11-07	en_US
dc.identifier.citation	Proceedings - IEEE International Conference on Multimedia and Expo, 2011	en_US
dc.identifier.isbn	9781612843490	en_US
dc.identifier.issn	1945-7871	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119459
dc.description.abstract	This paper considers a self-calibration approach to the estimation of motion parameters for an unknown camera used for video-based augmented reality. Whilst existing systems derive four SVD solutions of the essential matrix, which encodes the epipolar geometry between two camera views, this paper presents eight possible solutions derived from mathematical computation and geometrical analysis. The eight solutions not only reflect the position and orientation of the camera in static displacement but also the dynamic, relative orientation between the camera and an object in continuous motion. This paper details a novel algorithm that introduces three geometric constraints to determine the rotation and translation matrix from the eight possible essential matrix solutions. An OpenGL camera motion simulator is used to demonstrate and evaluate the reliability of the proposed algorithms; this directly visualizes the abstract computer vision parameters into real 3D. © 2011 IEEE.	en_US
dc.relation.ispartof	Proceedings - IEEE International Conference on Multimedia and Expo	en_US
dc.relation.isbasedon	10.1109/ICME.2011.6011989	en_US
dc.title	Eight solutions of the essential matrix for continuous camera motion tracking in video augmented reality	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	080106 Image Processing	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 Professional Practice and Leadership
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper considers a self-calibration approach to the estimation of motion parameters for an unknown camera used for video-based augmented reality. Whilst existing systems derive four SVD solutions of the essential matrix, which encodes the epipolar geometry between two camera views, this paper presents eight possible solutions derived from mathematical computation and geometrical analysis. The eight solutions not only reflect the position and orientation of the camera in static displacement but also the dynamic, relative orientation between the camera and an object in continuous motion. This paper details a novel algorithm that introduces three geometric constraints to determine the rotation and translation matrix from the eight possible essential matrix solutions. An OpenGL camera motion simulator is used to demonstrate and evaluate the reliability of the proposed algorithms; this directly visualizes the abstract computer vision parameters into real 3D. © 2011 IEEE.

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http://hdl.handle.net/10453/119459