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提出了一个健壮有效的网格模型多分辨分析方法 .该方法面向任意网格模型且不需要具有子分连通性 ,通过删除边和拆分点操作进行网格模型的向下采样和向上采样 ,将网格模型表示为由一个低分辨率的网格和一系列修改操作组成的多分辨模型 .该算法在向下采样时 ,重点考虑了简化误差对模型精度的影响 ,在生成网格多分辨模型时 ,将细化操作分解为对网格模型的几何修改信息和各细化操作之间的关系信息 ,确保了多分辨网格模型的健壮性 .实验结果证明了本算法的有效性 .
A robust and efficient multi-resolution analysis method for grid model is proposed. The proposed method is suitable for any grid model and does not require sub-sub-connectivity. Down-sampling and up-sampling grid models by deleting edges and splitting points, The grid model is represented as a multi-resolution model composed of a low-resolution grid and a series of modification operations.The algorithm focuses on the impact of the simplified error on model accuracy when down-sampling, Model, decomposing the refinement operation into the information about the geometric modification of the mesh model and the relationship between the refinement operations ensures the robustness of the multi-resolution mesh model.The experimental results show the effectiveness of the proposed algorithm.