Presentation 2020-03-16
Faster Approximate Nearest Neighbor Search using Label Information of Images
Onur Guler, Yusuke Matsui, Yoichi Sato,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Image retrieval systems commonly assume that the query images have the same distribution with the searched database. However, user queries are often limited by their surroundings and everyday life of the users. For example, a chef may search for kitchen equipment whereas a researcher would search for objects such as a computer and lab equipment. By reducing the search space for the image retrieval task according to user preferences, we can obtain a personalized, faster solution.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Image retrieval / User requirements / Personalization / Reduced search space
Paper # PRMU2019-85
Date of Issue 2020-03-09 (PRMU)

Conference Information
Committee PRMU / IPSJ-CVIM
Conference Date 2020/3/16(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Yoichi Sato(Univ. of Tokyo)
Vice Chair Toru Tamaki(Hiroshima Univ.) / Akisato Kimura(NTT)
Secretary Toru Tamaki(NTT) / Akisato Kimura(OMRON SINICX)
Assistant Yusuke Uchida(DeNA) / Takayoshi Yamashita(Chubu Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Special Interest Group on Computer Vision and Image Media
Language ENG-JTITLE
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Faster Approximate Nearest Neighbor Search using Label Information of Images
Sub Title (in English)
Keyword(1) Image retrieval
Keyword(2) User requirements
Keyword(3) Personalization
Keyword(4) Reduced search space
1st Author's Name Onur Guler
1st Author's Affiliation The University of Tokyo(UTokyo)
2nd Author's Name Yusuke Matsui
2nd Author's Affiliation The University of Tokyo(UTokyo)
3rd Author's Name Yoichi Sato
3rd Author's Affiliation The University of Tokyo(UTokyo)
Date 2020-03-16
Paper # PRMU2019-85
Volume (vol) vol.119
Number (no) PRMU-481
Page pp.pp.101-106(PRMU),
#Pages 6
Date of Issue 2020-03-09 (PRMU)