Fitting multiple connected ellipses to an image silhouette hierarchically

Xu, RYD; Kemp, M

Fitting multiple connected ellipses to an image silhouette hierarchically

Xu, RYD Kemp, M

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Image Processing, 2010, 19 (7), pp. 1673 - 1682
Issue Date:: 2010-07-01

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Field	Value	Language
dc.contributor.author	Xu, RYD	en_US
dc.contributor.author	Kemp, M	en_US
dc.date.issued	2010-07-01	en_US
dc.identifier.citation	IEEE Transactions on Image Processing, 2010, 19 (7), pp. 1673 - 1682	en_US
dc.identifier.issn	1057-7149	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13469
dc.description.abstract	In this paper, we seek to fit a model, specified in terms of connected ellipses, to an image silhouette. Some algorithms that have attempted this problem are sensitive to initial guesses and also may converge to a wrong solution when they attempt to minimize the objective function for the entire ellipse structure in one step. We present an algorithm that overcomes these issues. Our first step is to temporarily ignore the connections, and refine the initial guess using unconstrained Expectation-Maximization (EM) for mixture Gaussian densities. Then the ellipses are reconnected linearly. Lastly, we apply the Levenberg-Marquardt algorithm to fine-tune the ellipse shapes to best align with the contour. The fitting is achieved in a hierarchical manner based upon the joints of the model. Experiments show that our algorithm can robustly fit a complex ellipse structure to a corresponding shape for several applications. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Image Processing	en_US
dc.relation.isbasedon	10.1109/TIP.2010.2045071	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Fitting multiple connected ellipses to an image silhouette hierarchically	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	19	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1702 Cognitive Sciences	en_US
dc.location.activity	ISI:000278813800001	en_US
dc.location.activity	Barcelona, Spain
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
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	19	en_US

Abstract:

In this paper, we seek to fit a model, specified in terms of connected ellipses, to an image silhouette. Some algorithms that have attempted this problem are sensitive to initial guesses and also may converge to a wrong solution when they attempt to minimize the objective function for the entire ellipse structure in one step. We present an algorithm that overcomes these issues. Our first step is to temporarily ignore the connections, and refine the initial guess using unconstrained Expectation-Maximization (EM) for mixture Gaussian densities. Then the ellipses are reconnected linearly. Lastly, we apply the Levenberg-Marquardt algorithm to fine-tune the ellipse shapes to best align with the contour. The fitting is achieved in a hierarchical manner based upon the joints of the model. Experiments show that our algorithm can robustly fit a complex ellipse structure to a corresponding shape for several applications. © 2006 IEEE.

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http://hdl.handle.net/10453/13469