Presentation	2002/7/12 Kernel Face : Toward unified theory of invariant feature extraction Hitoshi SAKANO,
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Abstract(in English)	In this paper, we propose a novel paradigm for invariant feature extraction in similar object recognition. The paradigm is "ellimination of covariant element of feature makes invariant or robust feature against the variantion". Effectiveness of the paradigm is partially confirmed against illumination variations. In this report, we apply the methodology deduced from the paradigm to image variation caused by pose change. From the experimental results, we could not obtain a rigid evidence for effectiveness of the methodorogy. The expeimental results already showed potential of methodology. And the result clarify future problem.
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Keyword(in English)	face recognition / kernel PGA / subspace method / incariant feature extraction
Paper #	MVE2002-41
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Conference Information
Committee	MVE
Conference Date	2002/7/12(1days)
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Paper Information
Registration To	Media Experience and Virtual Environment (MVE)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Kernel Face : Toward unified theory of invariant feature extraction
Sub Title (in English)
Keyword(1)	face recognition
Keyword(2)	kernel PGA
Keyword(3)	subspace method
Keyword(4)	incariant feature extraction
1st Author's Name	Hitoshi SAKANO
1st Author's Affiliation	NTT Data Corporation()
Date	2002/7/12
Paper #	MVE2002-41
Volume (vol)	vol.102
Number (no)	220
Page	pp.pp.-
#Pages	4
Date of Issue