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<p>3D modeling technology is one of the most important research directions in computer vision, which is increasingly linked with digital sculpture art. Combined with the point cloud, a new type of image data, this paper innovatively proposes a multi-view 3D digital sculpture reconstruction model to realize the 3D digital sculpture reconstruction of point cloud data.3D digital sculpture reconstruction is mainly divided into two parts: point cloud data processing and 3D reconstruction. The former uses radius, statistical filtering, and bilateral filtering algorithms for point cloud data denoising and proposes an NDT alignment algorithm to integrate point cloud data. The latter triangulates the unreconstructed observation points introduced by the new image, uses beam method leveling to globally optimize the point cloud structure, and proposes incremental recovery and global recovery reconstruction methods, respectively. In the point cloud data alignment performance test, the reconstruction plotting time of the reconstruction model in this paper possesses a large improvement, and the proposed NDT algorithm outperforms the traditional algorithm in terms of accuracy and execution efficiency. In the reconstruction of architectural digital sculpture, the average error of the parts of the digital sculpture is 0.00775, and the maximum residual difference is at about 4.5 pixels. Hence, the sculpture’s accuracy and precision performance are better.</p>
</abstract>

3D modeling technology is one of the most important research directions in computer vision, which is increasingly linked with digital sculpture art. Combined with the point cloud, a new type of image data, this paper innovatively proposes a multi-view 3D digital sculpture reconstruction model to realize the 3D digital sculpture reconstruction of point cloud data.3D digital sculpture reconstruction is mainly divided into two parts: point cloud data processing and 3D reconstruction. The former uses radius, statistical filtering, and bilateral filtering algorithms for point cloud data denoising and proposes an NDT alignment algorithm to integrate point cloud data. The latter triangulates the unreconstructed observation points introduced by the new image, uses beam method leveling to globally optimize the point cloud structure, and proposes incremental recovery and global recovery reconstruction methods, respectively. In the point cloud data alignment performance test, the reconstruction plotting time of the reconstruction model in this paper possesses a large improvement, and the proposed NDT algorithm outperforms the traditional algorithm in terms of accuracy and execution efficiency. In the reconstruction of architectural digital sculpture, the average error of the parts of the digital sculpture is 0.00775, and the maximum residual difference is at about 4.5 pixels. Hence, the sculpture’s accuracy and precision performance are better.

Innovative design of digital sculpture art under 3D modeling technology

Guangdong University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Innovative design of digital sculpture art under 3D modeling technology"}

3D modeling technology is one of the most important research directions in computer vision, which is increasingly linked with digital sculpture art. Combined...

Innovative design of digital sculpture art under 3D modeling technology

Online veröffentlicht: 02. Juli 2024

Seitenbereich: -

Eingereicht: 29. Feb. 2024

Akzeptiert: 26. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1525

Schlüsselwörter
Digital sculpture, 3D modeling, Point cloud data, Beam method leveling, Bilateral filtering algorithm

© 2024 Shaowei Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Innovative design of digital sculpture art under 3D modeling technology

Online veröffentlicht: 02. Juli 2024

Seitenbereich: -

Eingereicht: 29. Feb. 2024

Akzeptiert: 26. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1525

SchlüsselwörterDigital sculpture, 3D modeling, Point cloud data, Beam method leveling, Bilateral filtering algorithm

© 2024 Shaowei Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Digital sculpture, 3D modeling, Point cloud data, Beam method leveling, Bilateral filtering algorithm