High-resolution Surface Reconstruction based on Multi-level Implicit Surface from Multiple Range Images

• Item type: Trans(1)
• 公開日: 2013-08-23
• タイトル: High-resolution Surface Reconstruction based on Multi-level Implicit Surface from Multiple Range Images
• タイトル / 言語: en
• タイトル: High-resolution Surface Reconstruction based on Multi-level Implicit Surface from Multiple Range Images
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [Regular Paper - Reserach Paper] range image, 3D point cloud, alignment, surface reconstruction, resolution enhancement
• 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: Graduate School of Information Science and Technology, the University of Tokyo
• 著者所属: Graduate School of Information Science and Technology, the University of Tokyo
• 著者所属: Graduate School of Information Science and Technology, the University of Tokyo
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, the University of Tokyo
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, the University of Tokyo
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, the University of Tokyo
• 著者名: Shohei, Noguchi; Yoshihiro, Watanabe; Masatoshi, Ishikawa
• 著者名(英): Shohei, Noguchi; Yoshihiro, Watanabe; Masatoshi, Ishikawa
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Sensing the 3D shape of a dynamic scene is not a trivial problem, but it is useful for various applications. Recently, sensing systems have been improved and are now capable of high sampling rates. However, particularly for dynamic scenes, there is a limit to improving the resolution at high sampling rates. In this paper, we present a method for improving the resolution of a 3D shape reconstructed from multiple range images acquired from a moving target. In our approach, the alignment and surface estimation problems are solved in a simultaneous estimation framework. Together with the use of an adaptive multi-level implicit surface for shape representation, this allows us to calculate the alignment by using shape features and surface estimation according to the amount of movement of the point clouds for each range image. By doing so, this approach realized simultaneous estimation more precisely than a scheme involving mere alternating estimation of shape and alignment. We present results of experiments for evaluating the reconstruction accuracy with different point cloud densities and noise levels.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Sensing the 3D shape of a dynamic scene is not a trivial problem, but it is useful for various applications. Recently, sensing systems have been improved and are now capable of high sampling rates. However, particularly for dynamic scenes, there is a limit to improving the resolution at high sampling rates. In this paper, we present a method for improving the resolution of a 3D shape reconstructed from multiple range images acquired from a moving target. In our approach, the alignment and surface estimation problems are solved in a simultaneous estimation framework. Together with the use of an adaptive multi-level implicit surface for shape representation, this allows us to calculate the alignment by using shape features and surface estimation according to the amount of movement of the point clouds for each range image. By doing so, this approach realized simultaneous estimation more precisely than a scheme involving mere alternating estimation of shape and alignment. We present results of experiments for evaluating the reconstruction accuracy with different point cloud densities and noise levels.
• 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: AA12628065
• 書誌情報: IPSJ Transactions on Computer Vision and Applications （CVA）; 巻 5, p. 143-152, 発行日 2013-08-23
• 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