Presentation | 2006-09-08 Experimental Investigation of Relation Between Near Neighbor Search Methods for Feature Vectors and Efficiency of Object Recognition Kazuto NOGUCHI, Tomohiro NAKAI, Koichi KISE, Masakazu IWAMURA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Efficiency of object recognition methods using local descriptors such as SIFT and PCA-SIFT depends largely on the speed of matching between feature vectors since images are described by a large number of feature vectors. Because the matching is considered to be "nearest neighbor (NN) search" of feature vectors, the problem is paraphrased by "how to make the NN search efficient". For the object recognition, it is required that the number of incorrect matching does not exceed that of correct matching. In other words, a certain number of incorrect matching is acceptable. This observation allows us to make NN search more efficient using approximate NN search with reduced distance calculation. For this purpose, we propose two methods: one is to eliminate feature vectors that require a number of distance calculations. The other is to use no distance calculation. From experimental results with 10,000 database images and 2,000 query images, it is shown that the proposed method is two to three times efficient as compared to a method using ANN and can achieve, recognition rate of 98% with 8.3 ms/query. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Object recognition / Approxiate nearest neighbor search / PCA-SIFT / ANN / LSH / Hash |
Paper # | PRMU2006-68 |
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Committee | PRMU |
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Conference Date | 2006/9/1(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
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) | Experimental Investigation of Relation Between Near Neighbor Search Methods for Feature Vectors and Efficiency of Object Recognition |
Sub Title (in English) | |
Keyword(1) | Object recognition |
Keyword(2) | Approxiate nearest neighbor search |
Keyword(3) | PCA-SIFT |
Keyword(4) | ANN |
Keyword(5) | LSH |
Keyword(6) | Hash |
1st Author's Name | Kazuto NOGUCHI |
1st Author's Affiliation | College of Engineering, Osaka Prefecture University() |
2nd Author's Name | Tomohiro NAKAI |
2nd Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
3rd Author's Name | Koichi KISE |
3rd Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
4th Author's Name | Masakazu IWAMURA |
4th Author's Affiliation | Graduate School of Engineering, Osaka Prefecture University |
Date | 2006-09-08 |
Paper # | PRMU2006-68 |
Volume (vol) | vol.106 |
Number (no) | 229 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |