Computational Models of Human Visual Attention and Their Implementations: A Survey

• KIMURA Akisato

  NTT Communication Science Laboratories, NTT Corporation

• YONETANI Ryo

  Graduate School of Informatics, Kyoto University

• HIRAYAMA Takatsugu

  Graduate School of Information Science, Nagoya University

抄録

We humans are easily able to instantaneously detect the regions in a visual scene that are most likely to contain something of interest. Exploiting this pre-selection mechanism called visual attention for image and video processing systems would make them more sophisticated and therefore more useful. This paper briefly describes various computational models of human visual attention and their development, as well as related psychophysical findings. In particular, our objective is to carefully distinguish several types of studies related to human visual attention and saliency as a measure of attentiveness, and to provide a taxonomy from several viewpoints such as the main objective, the use of additional cues and mathematical principles. This survey finally discusses possible future directions for research into human visual attention and saliency computation.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E96.D (3), 562-578, 2013

  一般社団法人 電子情報通信学会

キーワード

• human visual attention
• computational model
• saliency
• bottom-up
• top-down

詳細情報

• CRID: 1390001204379714816
• NII論文ID: 10031167446
• NII書誌ID: AA10826272
• DOI: 10.1587/transinf.e96.d.562
• ISSN: 17451361
• ISSN: 09168532
• HANDLE: 2433/171749
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E96.D/3/E96.D_562/_pdf
• 本文言語コード: en
• データソース種別:
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  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可