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Title:
smoothness-constrained face photo-sketch synthesis using sparse representation
Author: Chang Liang ; Deng Xiaoming ; Zhou Mingquan ; Duan Fuqing ; Wu Zhongke
Source: Proceedings - International Conference on Pattern Recognition
Conference Name: 21st International Conference on Pattern Recognition, ICPR 2012
Conference Date: November 11, 2012 - November 15, 2012
Issued Date: 2012
Conference Place: Tsukuba, Japan
Keyword: Convex optimization ; Optimization ; Pattern recognition
Indexed Type: EI
ISSN: 1051-4651
ISBN: 9784990644109
Department: (1) College of Information Science and Technology Beijing Normal University China; (2) Institute of Software Chinese Academy of Sciences China
Sponsorship: Science Council of Japan; Information Processing Society of Japan (IPSJ); Inst. Electron., Inf. Commun. Eng. (IEICE) Inf. Syst. Soc. (ISS); Japan Society for the Promotion of Science (JSPS); The Telecommunications Advancement Foundation
Abstract: Face photo-sketch and sketch-photo synthesis have important usages in law enforcement. It is challenging to synthesize face sketches from photos because the drawing techniques and styles of artists' depictions are hard to be learned. To synthesize face photos from sketches is also hard due to its ill-posed nature. In order to avoid mosaic effects in the existed photo-sketch methods, we propose a smoothness-constrained photo-sketch synthesis method via sparse representation. The work is an extension of the previous work[1]. The method is modeled as the minimization of an energy function, a large scale convex optimization problem with l1-norm constraint. Since previous optimization methods are infeasible to solve our problem, we propose an iterative optimization approach, which decomposes the large scale optimization into a sequence of small scale optimizations and solve them iteratively to obtain the approximated optimal solution. The same synthesis strategy can be also used to synthesize photos from sketches. Experiments show its effectiveness. © 2012 ICPR Org Committee.
English Abstract: Face photo-sketch and sketch-photo synthesis have important usages in law enforcement. It is challenging to synthesize face sketches from photos because the drawing techniques and styles of artists' depictions are hard to be learned. To synthesize face photos from sketches is also hard due to its ill-posed nature. In order to avoid mosaic effects in the existed photo-sketch methods, we propose a smoothness-constrained photo-sketch synthesis method via sparse representation. The work is an extension of the previous work[1]. The method is modeled as the minimization of an energy function, a large scale convex optimization problem with l1-norm constraint. Since previous optimization methods are infeasible to solve our problem, we propose an iterative optimization approach, which decomposes the large scale optimization into a sequence of small scale optimizations and solve them iteratively to obtain the approximated optimal solution. The same synthesis strategy can be also used to synthesize photos from sketches. Experiments show its effectiveness. © 2012 ICPR Org Committee.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15982
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Chang Liang,Deng Xiaoming,Zhou Mingquan,et al. smoothness-constrained face photo-sketch synthesis using sparse representation[C]. 见:21st International Conference on Pattern Recognition, ICPR 2012. Tsukuba, Japan. November 11, 2012 - November 15, 2012.
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