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High-Resolution Face Fusion for Gender Conversion

文献类型：期刊论文

作者Suo, Jinli2; Lin, Liang3; Shan, Shiguang1,4; Chen, Xilin1,4; Gao, Wen5
刊名IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
出版日期2011-03-01
卷号41期号:2页码:226-237
关键词And-Or graph face fusion gender conversion
ISSN号1083-4427
DOI10.1109/TSMCA.2010.2064304
英文摘要This paper presents an integrated face image fusion framework, which combines a hierarchical compositional paradigm with seamless image-editing techniques, for gender conversion. In our framework a high-resolution face is represented by a probabilistic graphical model that decomposes a human face into several parts (facial components) constrained by explicit spatial configurations (relationships). Benefiting from this representation, the proposed fusion strategy is able to largely preserve the face identity of each facial component while applying gender transformation. Given a face image, the basic idea is to select reference facial components from the opposite-gender group as templates and transform the appearance of the given image toward the selected facial components. Our fusion approach decomposes a face image into two parts-sketchable and nonsketchable ones. For the sketchable regions (e. g., the contours of facial components and wrinkle lines, etc.), we use a graph-matching algorithm to find the best templates and transform the structure (shape), while for the nonsketchable regions (e. g., the texture area of facial components, skin, etc.), we learn active appearance models and transform the texture attributes in the corresponding principal component analysis space. Both objective and subjective quantitative evaluation results on 200 Asian frontal-face images selected from the public Lotus Hill Image database show that the proposed approach is able to give plausible gender conversion results.
资助项目National Natural Science Foundation of China[60970156] ; National Natural Science Foundation of China[60728203] ; National High-Technology Research and Development Program of China[2007AA01Z340] ; National Program on Key Basic Research Projects[2009CB320902]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000286385800003
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/13041]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Suo, Jinli
作者单位1.Chinese Acad Sci, Inst Comp Technol, ICT ISVISION Joint Res & Dev Lab Face Recognit, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100190, Peoples R China
3.Sun Yat Sen Univ, Sch Software, Guangzhou 510275, Guangdong, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
5.Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
推荐引用方式
GB/T 7714		 Suo, Jinli,Lin, Liang,Shan, Shiguang,et al. High-Resolution Face Fusion for Gender Conversion[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS,2011,41(2):226-237.
APA Suo, Jinli,Lin, Liang,Shan, Shiguang,Chen, Xilin,&Gao, Wen.(2011).High-Resolution Face Fusion for Gender Conversion.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS,41(2),226-237.
MLA Suo, Jinli,et al."High-Resolution Face Fusion for Gender Conversion".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 41.2(2011):226-237.

入库方式： OAI收割

来源：计算技术研究所

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