Face sketch-photo synthesis based on support vector regression

Zhang, J; Wang, N; Gao, X; Tao, D; Li, X

Face sketch-photo synthesis based on support vector regression

Zhang, J Wang, N Gao, X Tao, D

Li, X

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Image Processing, ICIP, 2011, pp. 1125 - 1128
Issue Date:: 2011-12-01

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Field	Value	Language
dc.contributor.author	Zhang, J	en_US
dc.contributor.author	Wang, N	en_US
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	Proceedings - International Conference on Image Processing, ICIP, 2011, pp. 1125 - 1128	en_US
dc.identifier.isbn	9781457713033	en_US
dc.identifier.issn	1522-4880	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120476
dc.description.abstract	The existing face sketch-photo synthesis methods trend to lose some vital details more or less. In this paper, we propose a novel sketch-photo synthesis approach based on support vector regression (SVR) to handle this difficulty. First, we utilize an existing method to acquire the initial estimate of the synthesized image. Then, the final synthesized image is obtained by combining the initial estimate and the SVR based high frequency information together to further enhance the quality of synthesized image. Experimental results on the benchmark database and our new constructed database demonstrate that the proposed method can achieve significant improvement on perceptual quality. Moreover, the synthesized face images can obtain higher recognition rate when used in retrieval system. © 2011 IEEE.	en_US
dc.relation.ispartof	Proceedings - International Conference on Image Processing, ICIP	en_US
dc.relation.isbasedon	10.1109/ICIP.2011.6115625	en_US
dc.title	Face sketch-photo synthesis based on support vector regression	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and 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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

The existing face sketch-photo synthesis methods trend to lose some vital details more or less. In this paper, we propose a novel sketch-photo synthesis approach based on support vector regression (SVR) to handle this difficulty. First, we utilize an existing method to acquire the initial estimate of the synthesized image. Then, the final synthesized image is obtained by combining the initial estimate and the SVR based high frequency information together to further enhance the quality of synthesized image. Experimental results on the benchmark database and our new constructed database demonstrate that the proposed method can achieve significant improvement on perceptual quality. Moreover, the synthesized face images can obtain higher recognition rate when used in retrieval system. © 2011 IEEE.

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