Presentation | 2009-06-19 Memory Reduction with Bloomier Filters for Specific Object Recognition Katsufumi INOUE, Koichi KISE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Specific object recognition based on nearest neighbor search of feature vectors required a huge amount of memory to store all feature vectors for distance calculation. To solve this problem, we propose a memory reduction method for specific object recognition with a strategy of skipping the distance calculation of feature vectors. The proposed method is characterized by the use of Bloomier filters, which are far memory efficient than hash tables, for the storage of feature vectors. The proposed method is evaluated based on experiments of planar and 3D specific object recognition in comparison to a method with a hash table. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Bloomier filter / Bloom filter / Memory reduction / Specific object recognition / Local features |
Paper # | PRMU2009-56 |
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Committee | PRMU |
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Conference Date | 2009/6/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Memory Reduction with Bloomier Filters for Specific Object Recognition |
Sub Title (in English) | |
Keyword(1) | Bloomier filter |
Keyword(2) | Bloom filter |
Keyword(3) | Memory reduction |
Keyword(4) | Specific object recognition |
Keyword(5) | Local features |
1st Author's Name | Katsufumi INOUE |
1st Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University() |
2nd Author's Name | Koichi KISE |
2nd Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
Date | 2009-06-19 |
Paper # | PRMU2009-56 |
Volume (vol) | vol.109 |
Number (no) | 88 |
Page | pp.pp.- |
#Pages | 6 |
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