Presentation	2009-12-18 Compressed Pattern Recognition : A Framework of Pattern Measurement and Analysis Exploiting Sparsity Tomoya SAKAI,
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Abstract(in English)	This paper advocates integrating technologies of measurement, compression, encryption, and analysis of patterns into a consistent framework. Aiming to make the pattern recognition process more efficient, robust, and secure, we should develop comprehensively both techniques of pattern classification for compressed/encrypted data and data compression/encryption for pattern classification. Random projection is not only a possible means of the compression-encryption for pattern analysis, but a universal measurement in compressed sensing, i.e., an emerging signal acquisition technique exploiting sparsity. Some related works as well as practical algorithms are surveyed.
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Keyword(in English)	Random projection / Classification problem / Compressed sensing / Sparse representation
Paper #	PRMU2009-145
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Conference Information
Committee	PRMU
Conference Date	2009/12/10(1days)
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Paper Information
Registration To	Pattern Recognition and Media Understanding (PRMU)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	Compressed Pattern Recognition : A Framework of Pattern Measurement and Analysis Exploiting Sparsity
Sub Title (in English)
Keyword(1)	Random projection
Keyword(2)	Classification problem
Keyword(3)	Compressed sensing
Keyword(4)	Sparse representation
1st Author's Name	Tomoya SAKAI
1st Author's Affiliation	Inst. of Media and Info. Tech., Chiba Univ.()
Date	2009-12-18
Paper #	PRMU2009-145
Volume (vol)	vol.109
Number (no)	344
Page	pp.pp.-
#Pages	6
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