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Paper Abstract and Keywords
Presentation 2012-02-20 09:20
Dimensionality Reduction of Sparse Visual Features via Recoverable Projection for Large-Scale Image Retrieval
Zaixing He, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) For a large-scale image database, a main problem with bag-of-features-based image retrieval is the huge memory usage when the visual vocabulary size is large. In this paper, we solve this problem by reducing the dimensionality of the corresponding high-dimensional sparse feature vector via a projection matrix: Permuted Block Diagonal matrix. Then the obtained low-dimensional vector, instead of the original high-dimensional feature vector, is used as a new feature vector for image retrieval. Furthermore, because of the sparse nature, the original high-dimensional feature vector can be recovered when necessary, e.g., reranking the top retrieved images. A fast sparse recovery algorithm, Cross Low-dimensional Pursuit, is used for recovering the high-dimensional feature vector.
Keyword (in Japanese) (See Japanese page) 
(in English) Bag of features / recoverable projection / sparse recovery / permuted block diagonal matrix / cross low-dimensional pursuit / / /  
Reference Info. ITE Tech. Rep., vol. 36, no. 9, ME2012-39, pp. 1-6, Feb. 2012.
Paper # ME2012-39 
Date of Issue 2012-02-13 (HI, ME, AIT) 
ISSN Print edition: ISSN 1342-6893
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Conference Information
Committee ME AIT HI IEICE-IE IEICE-ITS  
Conference Date 2012-02-20 - 2012-02-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2012-02-ME-AIT-HI-IE-ITS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Dimensionality Reduction of Sparse Visual Features via Recoverable Projection for Large-Scale Image Retrieval 
Sub Title (in English)  
Keyword(1) Bag of features  
Keyword(2) recoverable projection  
Keyword(3) sparse recovery  
Keyword(4) permuted block diagonal matrix  
Keyword(5) cross low-dimensional pursuit  
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1st Author's Name Zaixing He  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Takahiro Ogawa  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Miki Haseyama  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2012-02-20 09:20:00 
Presentation Time 20 minutes 
Registration for ME 
Paper # HI2012-1, ME2012-39, AIT2012-1 
Volume (vol) vol.36 
Number (no) no.9 
Page pp.1-6 
#Pages
Date of Issue 2012-02-13 (HI, ME, AIT) 


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