Presentation	2014/2/6 Face recognition using Support vector machine Shintaro OBAYASHI, Shota FUNAKI, Yuki TSUKAGOSHI, Takuya KITAMURA,
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Abstract(in English)	In this paper, we demonstrate the effectiveness of support vector machines (SVMs) for the facial recognition system. we use least squares SVMs (LS-SVMs), sparse LS-SVM (SLS-SVM), fast SLS-SVM (FSLS-SVM) as the types of SVMs. These can train faster than the standard SVMs. So, the face recognition system using these types of SVMs, performs faster than that using the standard SVMs. In computer experiments, we compare the performance of this systems with that using subspace methods which are widely-used for the face recognition systems.
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Keyword(in English)	face recognition / support vector machine / subspace method
Paper #	CNR2013-34,PRMU2013-126
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Conference Information
Committee	CNR
Conference Date	2014/2/6(1days)
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Paper Information
Registration To	Cloud Network Robotics (CNR)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Face recognition using Support vector machine
Sub Title (in English)
Keyword(1)	face recognition
Keyword(2)	support vector machine
Keyword(3)	subspace method
1st Author's Name	Shintaro OBAYASHI
1st Author's Affiliation	Toyama National College of Technology()
2nd Author's Name	Shota FUNAKI
2nd Author's Affiliation	Toyama National College of Technology
3rd Author's Name	Yuki TSUKAGOSHI
3rd Author's Affiliation	Toyama National College of Technology
4th Author's Name	Takuya KITAMURA
4th Author's Affiliation	Toyama National College of Technology
Date	2014/2/6
Paper #	CNR2013-34,PRMU2013-126
Volume (vol)	vol.113
Number (no)	432
Page	pp.pp.-
#Pages	4
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