Presentation 2009-11-26
An adaptive color SIFT descriptor based on independent component analysis for image classification
Danni Ai, Xianhua Han, Xiang Ruan, Yen-Wei Chen,
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Abstract(in English) In this paper, we present a novel color independent components based SIFT descriptor (termed CIC-SIFT) for object/scene classification. We first learn an efficient color transformation matrix based on independent component analysis (ICA), which is adaptive to each category in a database. The ICA-based color transformation can enhance contrast between the objects and the background in an image. Then we compute CIC-SIFT descriptors over all three transformed color independent components. Since the ICA-based color transformation can boost the objects and suppress the background, the proposed CIC-SIFT can extract more effective and discriminative local features for object/scene classification. The comparison is performed among seven SIFT descriptors and the experimental classification results show that our proposed CIC-SIFT is superior to other conventional SIFT descriptors.
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Keyword(in English) CIC-SIFT descriptor / image classification / ICA-based transformation
Paper # PRMU2009-94
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Conference Information
Committee PRMU
Conference Date 2009/11/19(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An adaptive color SIFT descriptor based on independent component analysis for image classification
Sub Title (in English)
Keyword(1) CIC-SIFT descriptor
Keyword(2) image classification
Keyword(3) ICA-based transformation
1st Author's Name Danni Ai
1st Author's Affiliation Graduate School of Science and Enginnering, Ritumeikan University()
2nd Author's Name Xianhua Han
2nd Author's Affiliation Graduate School of Science and Enginnering, Ritumeikan University
3rd Author's Name Xiang Ruan
3rd Author's Affiliation Omron corporation
4th Author's Name Yen-Wei Chen
4th Author's Affiliation Graduate School of Science and Enginnering, Ritumeikan University
Date 2009-11-26
Paper # PRMU2009-94
Volume (vol) vol.109
Number (no) 306
Page pp.pp.-
#Pages 6
Date of Issue