Presentation 2004/9/3
A Vector Set Similarity Measure based on Bi-directional Mapping and Its Upper Bounds
Takanori YOKOYAMA, Toshinori WATANABE, Hisashi KOGA,
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Abstract(in English) We have proposed a fractal code retrieval method. There, we interpreted a fractal code as a vector set, and introduced a similarity measure between vector sets. This similarity measure required high computation cost. To reduce it, we proposed a method to use upper bounds of the similarity measure. In this report, we further improve the proposed upper bounds by using subsets of the vector sets, and introduce a new upper bound of the similarity measure. This new upper bound is a generalization of the already proposed upper bounds. After discussions on the details of the new upper bound, and we examine its properties through an image retrieval experiment.
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Paper # PRMU2004-72
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Committee PRMU
Conference Date 2004/9/3(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
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Title (in English) A Vector Set Similarity Measure based on Bi-directional Mapping and Its Upper Bounds
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1st Author's Name Takanori YOKOYAMA
1st Author's Affiliation Graduate School of Infomation Systems, University of Electro-Communications()
2nd Author's Name Toshinori WATANABE
2nd Author's Affiliation Graduate School of Infomation Systems, University of Electro-Communications
3rd Author's Name Hisashi KOGA
3rd Author's Affiliation Graduate School of Infomation Systems, University of Electro-Communications
Date 2004/9/3
Paper # PRMU2004-72
Volume (vol) vol.104
Number (no) 290
Page pp.pp.-
#Pages 6
Date of Issue