Paper Info
Title
Facial expressive image analysis by using nonlinear factorization model.
Abstract
Facial images captured by camera are usually influenced by several different kinds of factor, such as human identity, facial expression, and etc. Therefore facial expressive image analysis plays an important role in many different applications, such as expression recognition, face recognition with expressive images, facial expressive image synthesis and etc. In this paper, "human identity" and "facial expression" are regarded as two influence factors of face appearance, and a novel kernel-based bilinear factorization method is proposed to decouple the interaction from each other. The trained non-linear factorization model has been used for facial expressive image translation, and to person and/or expression recognition, and got promising results. In this paper the principle of our method is described and some preliminary experimental results are included.
Year
DOI
Venue
2004
10.1109/ICIG.2004.64
ICIG
Keywords
Field
DocType
bilinear factorization method,face recognition,human identity,facial expressive image translation,nonlinear factorization model,expression recognition,facial image,facial expressive image analysis,facial expressive image synthesis,facial expression,expressive image,image analysis,factor model
Image translation,Computer science,Artificial intelligence,Kernel (linear algebra),Computer vision,Facial recognition system,Face hallucination,Three-dimensional face recognition,Pattern recognition,Speech recognition,Facial expression,Factorization,Bilinear interpolation
Conference
ISBN
Citations 
PageRank 
0-7695-2244-0
2
0.39
References 
Authors
2
3
Name
Order
Citations
PageRank
Chuan Zhou1151.07
Yangzhou Du216913.85
Xueyin Lin336030.61