Presentation	2015/1/15 Query Feature Reduction For Multiple Instance Image Retrieval KEITA YUASA, TOSHIKAZU WADA,
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Abstract(in English)	For Multiple Instance Image Retrieval (MIIR), we have proposed index feature reduction method, which reduces the number of indexes attached to the image entries in the database. This method computes the importance measure representing the stability and the discrimination power of each feature by using the framework of Diverse Density and reduces the features having less importance measures. Through the experiments, this reduction drastically reduces the memory usage and retrieval accuracy, but the acceleration of retrieval speed is limited. This is because the number of nearest neighbor searches performed for each query is equivalent to the number of local features in the query image. This means that query feature reduction is required for the acceleration of image retrieval. This report presents a query feature reduction method for solving this problem.
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Paper #	Vol.2015-CVIM-195 No.29
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Committee	MVE
Conference Date	2015/1/15(1days)
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Paper Information
Registration To	Media Experience and Virtual Environment (MVE)
Language	JPN
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Title (in English)	Query Feature Reduction For Multiple Instance Image Retrieval
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1st Author's Name	KEITA YUASA
1st Author's Affiliation	Wakayama University()
2nd Author's Name	TOSHIKAZU WADA
2nd Author's Affiliation	Wakayama University
Date	2015/1/15
Paper #	Vol.2015-CVIM-195 No.29
Volume (vol)	vol.114
Number (no)	410
Page	pp.pp.-
#Pages	6
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