Color Independent Components Based SIFT Descriptors for Object/Scene Classification

• AI Dan-ni

  Ritsumeikan University

• HAN Xian-hua

  Ritsumeikan University

• RUAN Xiang

  Omron Corporation

• CHEN Yen-wei

  Ritsumeikan University

抄録

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.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E93-D (9), 2577-2586, 2010

  一般社団法人 電子情報通信学会

キーワード

• CIC-SIFT descriptor
• object/scene classification
• ICA-based transformation

詳細情報

• CRID: 1390282679353976960
• NII論文ID: 10027640676
• NII書誌ID: AA10826272
• DOI: 10.1587/transinf.e93.d.2577
• ISSN: 17451361
• ISSN: 09168532
• Web Site: http://www.jstage.jst.go.jp/article/transinf/E93.D/9/E93.D_9_2577/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可