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Bilateral recovering of sharp edges on feature-insensitive sampled meshes

机译:对特征不敏感的采样网格上的锐边进行双边恢复

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A variety of computer graphics applications sample surfaces of 3D shapes in a regular grid without making the sampling rate adaptive to the surface curvature or sharp features. Triangular meshes that interpolate or approximate these samples usually exhibit relatively big error around the insensitive sampled sharp features. This paper presents a robust general approach conducting bilateral filters to recover sharp edges on such insensitive sampled triangular meshes. Motivated by the impressive results of bilateral filtering for mesh smoothing and denoising, we adopt it to govern the sharpening of triangular meshes. After recognizing the regions that embed sharp features, we recover the sharpness geometry through bilateral filtering, followed by iteratively modifying the given mesh's connectivity to form single-wide sharp edges that can be easily detected by their dihedral angles. We show that the proposed method can robustly reconstruct sharp edges on feature-insensitive sampled meshes.
机译:各种计算机图形应用程序都在规则的网格中对3D形状的表面进行采样,而不会使采样率适应于表面曲率或尖锐特征。内插或近似这些样本的三角形网格通常在不敏感的采样锐利特征周围表现出较大的误差。本文提出了一种健壮的通用方法,该方法进行双边滤波器以恢复这种不敏感的采样三角形网格上的尖锐边缘。受双边滤波对网格平滑和去噪的令人印象深刻的结果激励,我们采用它来控制三角形网格的锐化。识别出嵌入了尖锐特征的区域后,我们通过双边滤波恢复了锐度几何形状,然后迭代修改给定网格的连接性以形成可以通过其二面角轻松检测到的单宽尖锐边缘。我们表明,提出的方法可以在特征不敏感的采样网格上稳健地重建锐利边缘。

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