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A New Feature-preserving Mesh-smoothing Algorithm

机译:一种新的保留特征的网格平滑算法

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We present a novel mesh denoising and smoothing method in this paper. Our approach starts by estimating the principal curvatures and mesh saliency value for each vertex. Then, we calculate the uniform principal curvature of each vertex based on the weighted average of local principal curvatures. After that, we use the weighted bi-quadratic Bezier surface to fit the neighborhood of each vertex using the least-square method and obtain the new vertex position by adjusting the parameters of the fitting surface. Experiments show that our smoothing method preserves the geometric feature of the original mesh model efficiently. Our approach also prevents the volume shrinkage of the input mesh and obtains smooth boundaries for non-closed mesh models.
机译:在本文中,我们提出了一种新颖的网格去噪和平滑方法。我们的方法首先估算每个顶点的主曲率和网格显着性值。然后,我们根据局部主曲率的加权平均值计算每个顶点的均匀主曲率。之后,我们使用加权的二次二次贝塞尔曲面使用最小二乘法拟合每个顶点的邻域,并通过调整拟合曲面的参数来获得新的顶点位置。实验表明,我们的平滑方法有效地保留了原始网格模型的几何特征。我们的方法还可以防止输入网格的体积收缩,并为非闭合网格模型获得平滑边界。

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