Presentation 2010-02-18
Instance-Based Localization Using Local Features
Zentaro ONO, Seiji HOTTA, Yaokai FENG, Seiichi UCHIDA,
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Abstract(in English) This paper analyzes location recognition by using local features and a simple nearest neighbor approach; after determining the location of each input local feature by nearest neighbor, the final recognition result of the entire input image is determined by voting. Specifically, if the input image is gets N local features, N location candidates are determined by the nearest neighbor (or k-nearest neighbor) from stored scenery images at known locations, and then the most major location is selected as the final location recognition result. Image block and SURF ware employed and examined as local features.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Localization / SURF / voting
Paper # PRMU2009-212
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Conference Information
Committee PRMU
Conference Date 2010/2/11(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) Instance-Based Localization Using Local Features
Sub Title (in English)
Keyword(1) Localization
Keyword(2) SURF
Keyword(3) voting
1st Author's Name Zentaro ONO
1st Author's Affiliation Graduate School of Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name Seiji HOTTA
2nd Author's Affiliation Tokyo University of Agriculture and Technology
3rd Author's Name Yaokai FENG
3rd Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
4th Author's Name Seiichi UCHIDA
4th Author's Affiliation Faculty of Information Science and Electrical Engineering, Kyushu University
Date 2010-02-18
Paper # PRMU2009-212
Volume (vol) vol.109
Number (no) 418
Page pp.pp.-
#Pages 6
Date of Issue