Facial Expression Recognition by Supervised ICA with Selective Prior

• Item type: SIG Technical Reports(1)
• 公開日: 2005-12-12
• タイトル: Facial Expression Recognition by Supervised ICA with Selective Prior
• タイトル / 言語: en
• タイトル: Facial Expression Recognition by Supervised ICA with Selective Prior
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: School of Information Science Japan Advanced Institute of Science and Technology
• 著者所属: School of Information Science Japan Advanced Institute of Science and Technology
• 著者所属(英): en
• 著者所属(英): School of Information Science, Japan Advanced Institute of Science and Technology
• 著者所属(英): en
• 著者所属(英): School of Information Science, Japan Advanced Institute of Science and Technology
• 著者名: Fan, Chen; Kazunori, Kotani
• 著者名(英): Fan, Chen; KazunoriKotani
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Feature selection is required when using the Independent Component Analysis (ICA) in feature extraction for pattern classification. Selection during ICA might provide a better candidate set of features. We propose a supervised ICA with a selective prior for the de-mixing coefficients so that those features with higher significance in discrimination could emerge easier during the learning. We formulate the learning rule for the supervised ICA in a form of the natural gradient approach and develop the algorithm of supervised ICA in facial expression analysis. The efficiency of the proposed algorithm has been investigated by numerical experiments.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Feature selection is required when using the Independent Component Analysis (ICA) in feature extraction for pattern classification. Selection during ICA might provide a better candidate set of features. We propose a supervised ICA with a selective prior for the de-mixing coefficients so that those features with higher significance in discrimination could emerge easier during the learning. We formulate the learning rule for the supervised ICA in a form of the natural gradient approach and develop the algorithm of supervised ICA in facial expression analysis. The efficiency of the proposed algorithm has been investigated by numerical experiments.
• 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: AN10438399
• 書誌情報: 情報処理学会研究報告オーディオビジュアル複合情報処理（AVM）; 巻 2005, 号 124(2005-AVM-051), p. 27-32, 発行日 2005-12-12
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会