Multiple representations-based face sketch-photo synthesis

Peng, C; Gao, X; Wang, N; Tao, D; Li, X; Li, J

Multiple representations-based face sketch-photo synthesis

Peng, C Gao, X Wang, N Tao, D

Li, X Li, J

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Neural Networks and Learning Systems, 2016, 27 (11), pp. 2201 - 2215
Issue Date:: 2016-11-01

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Field	Value	Language
dc.contributor.author	Peng, C	en_US
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Wang, N	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.contributor.author	Li, J	en_US
dc.date.issued	2016-11-01	en_US
dc.identifier.citation	IEEE Transactions on Neural Networks and Learning Systems, 2016, 27 (11), pp. 2201 - 2215	en_US
dc.identifier.issn	2162-237X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122661
dc.description.abstract	© 2012 IEEE. Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.	en_US
dc.relation	http://purl.org/au-research/grants/arc/FT130101457
dc.relation	http://purl.org/au-research/grants/arc/DP140102164
dc.relation	http://purl.org/au-research/grants/arc/LP140100569
dc.relation.ispartof	IEEE Transactions on Neural Networks and Learning Systems	en_US
dc.relation.isbasedon	10.1109/TNNLS.2015.2464681	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.subject.mesh	Face	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Algorithms	en_US
dc.subject.mesh	Neural Networks (Computer)	en_US
dc.subject.mesh	Databases, Factual	en_US
dc.subject.mesh	Pattern Recognition, Automated	en_US
dc.subject.mesh	Neural Networks, Computer	en_US
dc.title	Multiple representations-based face sketch-photo synthesis	en_US
dc.type	Journal Article
utslib.citation.volume	11	en_US
utslib.citation.volume	27	en_US
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.issue	11	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

© 2012 IEEE. Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

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

http://hdl.handle.net/10453/122661