Presentation	2011-02-17 Large-Scale Generic Image Recognition and Image Representation Tatsuya HARADA,
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Abstract(in English)	In recent years, it is becoming possible to obtain a large amount of image and additional information (e.g., tags) from the Internet. The generic image recognition learning from a large-scale image dataset becomes an active area in the computer vision and the multimedia communities. In this paper, we introduce the trend of the large-scale generic image recognition, and describe the leading-edge image representation methods, which can achieve impressive classification accuracy even with the linear classifier.
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Keyword(in English)	image annotation / object recognition / scene recognition / image feature / scalability
Paper #	PRMU2010-218
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Conference Information
Committee	PRMU
Conference Date	2011/2/10(1days)
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Paper Information
Registration To	Pattern Recognition and Media Understanding (PRMU)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Large-Scale Generic Image Recognition and Image Representation
Sub Title (in English)
Keyword(1)	image annotation
Keyword(2)	object recognition
Keyword(3)	scene recognition
Keyword(4)	image feature
Keyword(5)	scalability
1st Author's Name	Tatsuya HARADA
1st Author's Affiliation	Graduate School of Information Science and Technology, The University of Tokyo:JST PRESTO()
Date	2011-02-17
Paper #	PRMU2010-218
Volume (vol)	vol.110
Number (no)	414
Page	pp.pp.-
#Pages	14
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