Compact Fundamental Matrix Computation

• Item type: Trans(1)
• 公開日: 2010-03-11
• タイトル: Compact Fundamental Matrix Computation
• タイトル / 言語: en
• タイトル: Compact Fundamental Matrix Computation
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Research Paper
• 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: Okayama University
• 著者所属: Toyohashi University of Technology
• 著者所属(英): en
• 著者所属(英): Okayama University
• 著者所属(英): en
• 著者所属(英): Toyohashi University of Technology
• 著者名: Kenichi, Kanatani; Yasuyuki, Sugaya
• 著者名(英): Kenichi, Kanatani; Yasuyuki, Sugaya
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: A very compact algorithm is presented for fundamental matrix computation from point correspondences over two images. The computation is based on the maximum likelihood (ML) principle, minimizing the reprojection error. The rank constraint is incorporated by the EFNS procedure. Although our algorithm produces the same solution as all existing ML-based methods, it is probably the most practical of all, being small and simple. By numerical experiments, we confirm that our algorithm behaves as expected.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: A very compact algorithm is presented for fundamental matrix computation from point correspondences over two images. The computation is based on the maximum likelihood (ML) principle, minimizing the reprojection error. The rank constraint is incorporated by the EFNS procedure. Although our algorithm produces the same solution as all existing ML-based methods, it is probably the most practical of all, being small and simple. By numerical experiments, we confirm that our algorithm behaves as expected.
• 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: AA12394973
• 書誌情報: IPSJ Transactions on Computer Vision and Applications（CVA）; 巻 2, p. 59-70, 発行日 2010-03-11
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-6695
• 出版者 / 言語: ja
• 出版者: 情報処理学会