ハイブリッド画像理解システムにおける選択的注意モデルのパラメータチューニング

• 三ツ森 芳幸

  メディアドライブ株式会社新技術開発研究所

• 大森 隆司

  北海道大学大学院情報科学研究科複合情報学専攻

書誌事項

タイトル別名

• Parameter Tuning of the Selective Attention Model in a Hybrid Image Understanding System

抄録

Fukushima's Selective Attention Model is a model of biological vision system. It has engineering merit of deformation and position shift tolerant recognition and recollection of the recognized object in an input image. Based on this feature, we have proposed a method for hybrid image understanding in which each object is recognized, recollected and segmented sequentially even when the objects are overlapped and occluded. However, parameter setting for the fine object recollection is difficult with the Selective Attention Model and parameters search is necessary to tune the given image. In this paper, we propose a method for the parameter search based on an evaluation of image recollection precision in the hybrid image understanding process. A computer simulation result demonstrates the validity of the proposed method.

収録刊行物

• 日本神経回路学会誌

  日本神経回路学会誌 12 (1), 3-10, 2005

  日本神経回路学会

詳細情報

• CRID: 1390282679440139904
• NII論文ID: 10015446320
• NII書誌ID: AA11658570
• DOI: 10.3902/jnns.12.3
• ISSN: 18830455
• ISSN: 1340766X
• 本文言語コード: ja
• 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