Color Independent Components Based SIFT Descriptors for Object/Scene Classification
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2010-09-01
著者
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Ruan Xiang
Omron Corporation
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Ruan Xiang
Omron Corp. Kusatsu‐shi Jpn
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Ai Danni
Graduate School of Science and Engineering, Ritsumeikan University
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AI Dan-ni
Ritsumeikan University
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HAN Xian-hua
Ritsumeikan University
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CHEN Yen-wei
Ritsumeikan University
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Han Xianhua
Graduate School Of Science And Engineering Ritsumeikan University
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Han Xian‐hua
Ritsumeikan Univ. Kusatsu‐shi Jpn
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Chen Yen
College Of Information Science And Engineering Ritsumeikan University
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Chen Y‐w
College Of Information Science And Engineering Ritsumeikan University
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Han Xian‐hua
College Of Information Science And Engineering Ritsumeikan University
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Chen Yen-wei
College Of Information And Science Ristumeikan University
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Chen Yen-wei
College Of Information And Science Ritsumeikan University
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Han Xianhua
College of Information Science and Engineering, Ritsumeikan University
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