新媒体时代的现代雕塑数字化设计研究

IF 3.1 Q1 Mathematics
Xiaozhong Chen, Chaoyang Zhang
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引用次数: 0

摘要

本文致力于探索新媒体时代的现代雕塑数字化设计,解决传统雕塑在数字化转型中遇到的挑战和机遇。考虑到数字技术给艺术创作带来的革新,通过对三维雕塑表面几何参数的精确分析和特征描述,引入先进的 NURBS 方法和 FCM 聚类算法,提高雕塑数字化的精度和效率。利用非均匀有理 B-样条曲线(NURBS)和模糊 C-均值(FCM)聚类算法分析了三维雕塑的表面几何参数和特征。NURBS 方法可以有效地表示雕塑的高阶曲面,而 FCM 聚类算法则在曲面分区规划中表现出高效的性能。基于 NURBS 的 FCM 算法可将点云拼接的均方根误差降低到 0.0853 毫米,迭代次数减少到 3 次,算法运行时间缩短到 18.46 秒。数字雕塑应用实践表明,该方法提高了工作效率,降低了生产成本。本研究提出的数字化设计方法为现代雕塑的生产和创作提供了一种新的途径,有助于传统雕塑艺术在新媒体时代的发展和传承。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Digital Design of Modern Sculpture in New Media Era
This paper is dedicated to exploring the digital design of modern sculpture in the era of new media, addressing the challenges and opportunities encountered by traditional sculpture in digital transformation. Considering the innovation brought by digital technology to artistic creation, the precision and efficiency of sculpture digitization are improved by introducing advanced NURBS method and FCM clustering algorithm through precise analysis and characterization of surface geometric parameters of three-dimensional sculptures. The surface geometric parameters and characteristics of three-dimensional sculptures are analyzed using non-uniform rational B-spline (NURBS) and fuzzy C-mean (FCM) clustering algorithms. The high-order surfaces of the sculptures can be represented effectively by the NURBS method, whereas the FCM clustering algorithms exhibit highly efficient performance in surface partitioning planning. The NURBS-based FCM algorithm can reduce the root-mean-square error of point cloud splicing to 0.0853 mm, reduce the number of iterations to 3, and shorten the algorithm’s running time to 18.46 seconds. The practice of digital sculpture application shows that the method improves work efficiency and reduces production costs. The digital design method proposed in this study provides a new way of producing and creating modern sculpture, which helps develop and preserve traditional sculpture art in the new media era.
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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