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Adaptive fitting algorithm of progressive interpolation for Loop subdivision surface:

机译:Loop细分曲面的渐进插值自适应拟合算法:

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摘要

Subdivision surface and data fitting have been applied in data compression and data fusion a lot recently. Moreover, subdivision schemes have been successfully combined into multi-resolution analysis and wavelet analysis. This makes subdivision surfaces attract more and more attentions in the field of geometry compression. Progressive interpolation subdivision surfaces generated by approximating schemes were presented recently. When the number of original vertices becomes huge, the convergence speed becomes slow and computation complexity becomes huge. In order to solve these problems, an adaptive progressive interpolation subdivision scheme is presented in this article. The vertices of control mesh are classified into two classes: active vertices and fixed ones. When precision is given, the two classes of vertices are changed dynamically according to the result of each iteration. Only the active vertices are adjusted, thus the class of active vertices keeps running down while the fixed ones keep rising, which saves computation greatly. Furthermore, weights are assigned to these vertices to accelerate convergence speed. Theoretical analysis and numerical examples are also given to illustrate the correctness and effectiveness of the method.
机译:细分表面和数据拟合最近已在数据压缩和数据融合中得到了广泛应用。此外,细分方案已成功地组合到多分辨率分析和小波分析中。这使得细分曲面在几何压缩领域吸引了越来越多的关注。最近介绍了由近似方案生成的渐进插值细分曲面。当原始顶点数变大时,收敛速度变慢并且计算复杂度变大。为了解决这些问题,本文提出了一种自适应渐进插值细分方案。控制网格的顶点分为两类:活动顶点和固定顶点。当给出精度时,两类顶点会根据每次迭代的结果动态变化。仅对活动顶点进行调整,因此活动顶点的类别保持递减,而固定顶点的类别持续上升,从而大大节省了计算量。此外,将权重分配给这些顶点以加快收敛速度​​。理论分析和数值算例也说明了该方法的正确性和有效性。

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