Galois’ Lattices as a Classification Technique for Image Retrieval

• Item type: Trans(1)
• 公開日: 2005-12-15
• タイトル: Galois’ Lattices as a Classification Technique for Image Retrieval
• タイトル / 言語: en
• タイトル: Galois’ Lattices as a Classification Technique for Image Retrieval
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 研究論文
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Atlas-GRIM Team INRIA & LINA Graduate School of Engineering Tokyo Metropolitan University
• 著者所属: Atlas-GRIM Team INRIA & LINA
• 著者所属: Graduate School of Engineering Tokyo Metropolitan University
• 著者所属: Graduate School of Engineering Tokyo Metropolitan University
• 著者所属(英): en
• 著者所属(英): Atlas-GRIM Team INRIA & LINA,Graduate School of Engineering Tokyo Metropolitan University
• 著者所属(英): en
• 著者所属(英): Atlas-GRIM Team INRIA & LINA
• 著者所属(英): en
• 著者所属(英): Graduate School of Engineering Tokyo Metropolitan University
• 著者所属(英): en
• 著者所属(英): Graduate School of Engineering Tokyo Metropolitan University
• 著者名: Erwan, Loisant; Jos´e, Martinez; Hiroshi, Ishikawa; Kaoru, Katayama
• 著者名(英): Erwan, Loisant; Jos´e, Martinez; Hiroshi, Ishikawa; Kaoru, Katayama
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Going one step ahead feedback querying in integrating users into a search process navigation is the more recent approach to finding images in a large image collection by using contentbased information. Rather than using queries or going into a feedback querying process that would be both heavy in terms of human-computer interaction and computer processing time navigation on a pre-computed data structure is easier and smoother for the user. In particular we found Galois’ lattices to be convenient structures for that purpose. However while properties extracted from images are usually real-valued data most of the time a navigation structure has to deal with binary links from an image (or a group of images) to another. A trivial solution to get a binary relationship from real-valued data is to apply a threshold but this solution not only leads to a loss of information but also tends to create sparse areas in the lattice. In this paper we propose a technique to incrementally build a Galois’ lattice from real-valued properties by taking into account the existing structure thus limiting the size of the lattice by avoiding the creation of sparse nodes. Experiments showed that this technique produces a navigation structure of better quality making search process faster and more efficient thus improving user’s experience.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Going one step ahead feedback querying in integrating users into a search process, navigation is the more recent approach to finding images in a large image collection by using contentbased information. Rather than using queries or going into a feedback querying process that would be both heavy in terms of human-computer interaction and computer processing time, navigation on a pre-computed data structure is easier and smoother for the user. In particular, we found Galois’ lattices to be convenient structures for that purpose. However, while properties extracted from images are usually real-valued data, most of the time a navigation structure has to deal with binary links from an image (or a group of images) to another. A trivial solution to get a binary relationship from real-valued data is to apply a threshold, but this solution not only leads to a loss of information but also tends to create sparse areas in the lattice. In this paper, we propose a technique to incrementally build a Galois’ lattice from real-valued properties by taking into account the existing structure, thus limiting the size of the lattice by avoiding the creation of sparse nodes. Experiments showed that this technique produces a navigation structure of better quality, making search process faster and more efficient, thus improving user’s experience.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11464847
• 書誌情報: 情報処理学会論文誌データベース（TOD）; 巻 46, 号 SIG18(TOD28), p. 16-28, 発行日 2005-12-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7799
• 出版者 / 言語: ja
• 出版者: 情報処理学会