Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
3D reconstruction of non-structural surface of a stiffened hull plate based on RGB-D images
https://orcid.org/0000-0002-9112-0408
Deformation measurement of hull structure is of great significance for enhancing the quality of shipbuilding. In this paper, a three-dimensional (3D) reconstruction method based on RGB-D images is presented for non-structural surface of a stiffened hull plate. The algorithm for object surface region nodes (OSRN) is proposed to extract the features of point clouds and generate higher-order fitting surface model. Firstly, random sample consensus (RANSAC) algorithm and least square method are applied to eliminate the noise of point clouds. Spatial position of targets in RGB image and singular value decomposition (SVD) are utilized to accomplish the registration of point clouds from multiple camera views. Then, the point clouds data are clustered and fused to fit the quadric surface. On this basis, the 3D surface model is reconstructed through higher-order panel element. Two comparative experiments, including the measurements via the RGB-D camera and 3D Laser Scanner, are carried out to verify the applicability and accuracy of the proposed method.
3D reconstruction of non-structural surface of a stiffened hull plate based on RGB-D images
https://orcid.org/0000-0002-9112-0408
Deformation measurement of hull structure is of great significance for enhancing the quality of shipbuilding. In this paper, a three-dimensional (3D) reconstruction method based on RGB-D images is presented for non-structural surface of a stiffened hull plate. The algorithm for object surface region nodes (OSRN) is proposed to extract the features of point clouds and generate higher-order fitting surface model. Firstly, random sample consensus (RANSAC) algorithm and least square method are applied to eliminate the noise of point clouds. Spatial position of targets in RGB image and singular value decomposition (SVD) are utilized to accomplish the registration of point clouds from multiple camera views. Then, the point clouds data are clustered and fused to fit the quadric surface. On this basis, the 3D surface model is reconstructed through higher-order panel element. Two comparative experiments, including the measurements via the RGB-D camera and 3D Laser Scanner, are carried out to verify the applicability and accuracy of the proposed method.
3D reconstruction of non-structural surface of a stiffened hull plate based on RGB-D images
https://orcid.org/0000-0002-9112-0408
Deformation measurement of hull structure is of great significance for enhancing the quality of shipbuilding. In this paper, a three-dimensional (3D) reconstruction method based on RGB-D images is presented for non-structural surface of a stiffened hull plate. The algorithm for object surface region nodes (OSRN) is proposed to extract the features of point clouds and generate higher-order fitting surface model. Firstly, random sample consensus (RANSAC) algorithm and least square method are applied to eliminate the noise of point clouds. Spatial position of targets in RGB image and singular value decomposition (SVD) are utilized to accomplish the registration of point clouds from multiple camera views. Then, the point clouds data are clustered and fused to fit the quadric surface. On this basis, the 3D surface model is reconstructed through higher-order panel element. Two comparative experiments, including the measurements via the RGB-D camera and 3D Laser Scanner, are carried out to verify the applicability and accuracy of the proposed method.
3D reconstruction of non-structural surface of a stiffened hull plate based on RGB-D images
Li, Jun (Autor:in) / Chen, Zhen (Autor:in) / Li, Dongyang (Autor:in) / Sun, Chao (Autor:in) / Ding, Yuhang (Autor:in)
01.05.2023
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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