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How many sample points are sufficient for 3D model surface representation and accurate mesh simplification?

机译:3D模型表面表示和准确的网格简化是多少个样本点?

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摘要

Growing of 3D model products and its applications in mobile devices and multimedia tools increases demands to establish an effective approach for representing and compressing of these models. In this paper, we propose an algorithm to simplify a complex 3D mesh and reduce the number of vertices by re-sampling the mesh based on the Nyquist theorem in order to find the sufficient number of samples that is necessary to save the quality of the reconstructed mesh, precisely. To achieve the optimum number of samples in the simplified mesh, both maximum curvature (C_(max)) and minimum curvature (C_(min)) in the original mesh are employed for adaptive sampling in different directions. Since the samples are adaptively taken regarding the curvature variations in both directions of maximum and minimum curvatures, the least number of vertices is obtained to represent the model. Hence, the method not only simplifies the complex mesh, but also preserves fine scale features in the mesh. The proposed method is applied to different complex mesh surfaces. The experimental results demonstrate that our proposed framework can represent a mesh surface with the least number of samples besides preserving important features in the surface.
机译:3D模型产品的增长及其在移动设备和多媒体工具中的应用增加了要求建立一种有效的代表和压缩这些模型的方法。在本文中,我们提出了一种算法来简化复杂的3D网格,并通过基于奈奎斯特定理重新采样网格来减少顶点的数量,以便找到节省重建质量所需的足够数量的样本筛网,精确。为了在简化网格中实现最佳数量,最大曲率(C_(最大))和原始网格中的最小曲率(C_(min))用于在不同方向上的自适应采样。由于样本对最大和最小曲率的两个方向上的曲率变化自适应地进行,因此获得最少的顶点以表示模型。因此,该方法不仅简化了复杂的网格,而且还保留了网格中的精细规模特征。该方法应用于不同的复杂网状表面。实验结果表明,我们所提出的框架可以代表具有最少数量的样品的网状表面,除了在表面中保持重要特征。

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