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	Facial expression synthesis and recognition using a kernel-based factorization model
	Zhou Chuan ; Lin Xueyin
	2010-05-06 ; 2010-05-06
关键词	Practical Theoretical or Mathematical/ face recognition matrix decomposition/ facial expression synthesis facial recognition sample-based method human identity kernel-based bilinear factorization model/ B6135E Image recognition B0210 Algebra C1250M Image recognition C1110 Algebra
中文摘要	Facial expression synthesis is an important technique in human computer interactions. The traditional 3-D reconstruction method using a face physiology model requires very complex computations, therefore, a sample-based method was developed to synthesize realistic facial expressions. To translate facial expressions, the model treats "human identity" and "facial expression" as two factors influencing the face appearance, with a kernel-based bilinear factorization model used to decouple their interactions. The distribution features of the subspaces obtained by factorization were used to develop a method to recognize people and expressions. Test results show that the method can successfully translate realistic facial expressions from one person to another.
语种	中文 ; 中文
出版者	Tsinghua Univ. Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9840]
专题	清华大学
推荐引用方式 GB/T 7714	Zhou Chuan,Lin Xueyin. Facial expression synthesis and recognition using a kernel-based factorization model[J],2010, 2010.
APA	Zhou Chuan,&Lin Xueyin.(2010).Facial expression synthesis and recognition using a kernel-based factorization model..
MLA	Zhou Chuan,et al."Facial expression synthesis and recognition using a kernel-based factorization model".(2010).

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