Presentation	2004/11/11 Facial expression analysis by ICA-EMC considering class-features Isao EGUCHI, Kazunori KOTANI,
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Abstract(in English)	This report includes ICA (Independent Component Analysis) as one of method for facial expression analysis. The basis derived by ICA is nonorthogonality, has a possibility of representing facial expression-features with accuracy compared to PCA. Since ICA does not derive the basis considered class-features, is expected to separate each expression-classes by considering class-features. This report describes a new method named ICA-EMC. ICA-EMC uses the basis from EMC (Eigen-space Method based on Class-features) for ICA in facial expression analysis.
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Keyword(in English)	facial expression analysis / eigen-space method / independent component analysis
Paper #	PRMU2004-98,HIP2004-38
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Conference Information
Committee	HIP
Conference Date	2004/11/11(1days)
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Paper Information
Registration To	Human Information Processing (HIP)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Facial expression analysis by ICA-EMC considering class-features
Sub Title (in English)
Keyword(1)	facial expression analysis
Keyword(2)	eigen-space method
Keyword(3)	independent component analysis
1st Author's Name	Isao EGUCHI
1st Author's Affiliation	School of Information Science, Japan Advanced Institute of Science and Technology()
2nd Author's Name	Kazunori KOTANI
2nd Author's Affiliation	School of Information Science, Japan Advanced Institute of Science and Technology
Date	2004/11/11
Paper #	PRMU2004-98,HIP2004-38
Volume (vol)	vol.104
Number (no)	449
Page	pp.pp.-
#Pages	6
Date of Issue