A Multiscale Decomposition of Point-sampled 3D Objects

• Item type: SIG Technical Reports(1)
• 公開日: 2005-05-20
• タイトル: A Multiscale Decomposition of Point-sampled 3D Objects
• タイトル / 言語: en
• タイトル: A Multiscale Decomposition of Point-sampled 3D Objects
• 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: Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属: Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属: Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属: Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Engineering Tokyo Institute of Technology
• 著者名: Hamid, Laga; Hiroki, Takahashi; Suguru, Saito; Masayuki, Nakajima
• 著者名(英): Hamid, Laga; Hiroki, Takahashi; Suguru, Saito; Masayuki, Nakajima
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In this paper we propose a simple method for the decomposition of point-sampled 3D objects into its basic components. Our approach is based on recent methods for fuzzy clustering and hierarchical decomposition of 3D meshes where we use instead a k-nearest neighbor graph of the point cloud. Our approach proceeds in two steps: We first encode the geometric properties of the 3D shape into an inter-surfel distance matrix. The distance between two surfels takes into account the geodesic distance the angular distance to measure the shape convexity and the surface variation. Then we apply a clustering algorithm on the distance matrix to extract the different components of the input surfels. We demonstrate the efficiency of the proposed approach on a collection of point sampled 3D objects.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In this paper we propose a simple method for the decomposition of point-sampled 3D objects into its basic components. Our approach is based on recent methods for fuzzy clustering and hierarchical decomposition of 3D meshes, where we use instead a k-nearest neighbor graph of the point cloud. Our approach proceeds in two steps: We first encode the geometric properties of the 3D shape into an inter-surfel distance matrix. The distance between two surfels takes into account the geodesic distance, the angular distance to measure the shape convexity and the surface variation. Then, we apply a clustering algorithm on the distance matrix to extract the different components of the input surfels. We demonstrate the efficiency of the proposed approach on a collection of point sampled 3D objects.
• 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: AN10100541
• 書誌情報: 情報処理学会研究報告グラフィクスとCAD（CG）; 巻 2005, 号 44(2005-CG-119), p. 31-36, 発行日 2005-05-20
• 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