Presentation 2007-01-19
An Accelerated Nearest Neighbor Image Search by Principal Component Tree using Integral Image
Junya FUJIWARA, Hidetaka ARAI, Takekazu KATO, Toshikazu WADA,
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Abstract(in English) Nearest Neighbor (NN) search is essential for case/instance based reasoning. Most NN search methods proposed so far are based on NN candidate narrowing and these methods degenerates to brute force search in highdimensional space over 30D. For solving this problem, we have been proposed PC-tree that is modifed the kd-tree by replacing a space dividing axis by a principal axis of prototypes. However, the method achieved insufficient accelaration because the method required inner producets between an input image and each dividing axis. In this paper, we propose an accelerated inner products between images by using integral image and apply it to the nearest neighbor image search with PC-tree.
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Keyword(in English) nearest neighbor search / principal component analisys / space decomposition / integral image
Paper # PRMU2006-203
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Committee PRMU
Conference Date 2007/1/12(1days)
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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) An Accelerated Nearest Neighbor Image Search by Principal Component Tree using Integral Image
Sub Title (in English)
Keyword(1) nearest neighbor search
Keyword(2) principal component analisys
Keyword(3) space decomposition
Keyword(4) integral image
1st Author's Name Junya FUJIWARA
1st Author's Affiliation Faculty of System Engineering, Wakayama University()
2nd Author's Name Hidetaka ARAI
2nd Author's Affiliation Faculty of System Engineering, Wakayama University
3rd Author's Name Takekazu KATO
3rd Author's Affiliation Faculty of System Engineering, Wakayama University
4th Author's Name Toshikazu WADA
4th Author's Affiliation Faculty of System Engineering, Wakayama University
Date 2007-01-19
Paper # PRMU2006-203
Volume (vol) vol.106
Number (no) 470
Page pp.pp.-
#Pages 6
Date of Issue