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锐化与弯曲:恢复由特征不敏感采样生成的三角形网格中的弯曲尖锐边缘。

Sharpen&Bend: recovering curved sharp edges in triangle meshes produced by feature-insensitive sampling.

作者信息

Attene Marco, Falcidieno Bianca, Rossignac Jarek, Spagnuolo Michela

机构信息

Istituto di Matematica Applicata e Tecnologie Informatiche, sez di Genova, Consiglio Nazionale delle Ricerche, Via De Marini 6, Torre di Francia, 16149, Genova, Italy.

出版信息

IEEE Trans Vis Comput Graph. 2005 Mar-Apr;11(2):181-92. doi: 10.1109/TVCG.2005.34.

DOI:10.1109/TVCG.2005.34
PMID:15747641
Abstract

Various acquisition, analysis, visualization, and compression approaches sample surfaces of 3D shapes in a uniform fashion without any attempt to align the samples with sharp edges or to adapt the sampling density to the surface curvature. Consequently, triangle meshes that interpolate these samples usually chamfer sharp features and exhibit a relatively large error in their vicinity. We present two new filters that improve the quality of these resampled models. EdgeSharpener restores the sharp edges by splitting the chamfer edges and forcing the new vertices to lie on intersections of planes extending the smooth surfaces incident upon these chamfers. Bender refines the resulting triangle mesh using an interpolating subdivision scheme that preserves the sharpness of the recovered sharp edges while bending their polyline approximations into smooth curves. A combined Sharpen&Bend postprocessing significantly reduces the error produced by feature-insensitive sampling processes. For example, we have observed that the mean-squared distortion introduced by the SwingWrapper remeshing-based compressor can often be reduced by 80 percent executing EdgeSharpener alone after decompression. For models with curved regions, this error may be further reduced by an additional 60 percent if we follow the EdgeSharpening phase by Bender.

摘要

各种采集、分析、可视化和压缩方法以统一的方式对三维形状的表面进行采样,而没有任何尝试将样本与尖锐边缘对齐,或使采样密度适应表面曲率。因此,对这些样本进行插值的三角形网格通常会对尖锐特征进行倒角,并在其附近表现出相对较大的误差。我们提出了两种新的滤波器,可提高这些重新采样模型的质量。EdgeSharpener通过分割倒角边并迫使新顶点位于延伸到这些倒角的光滑表面的平面的交点上,来恢复尖锐边缘。Bender使用插值细分方案对生成的三角形网格进行细化,该方案在将折线近似弯曲成平滑曲线的同时,保留恢复的尖锐边缘的锐度。Sharpen&Bend组合后处理显著减少了由特征不敏感采样过程产生的误差。例如,我们观察到,在解压缩后仅执行EdgeSharpener,基于SwingWrapper重网格化的压缩器引入的均方失真通常可以减少80%。对于具有弯曲区域的模型,如果在EdgeSharpening阶段之后使用Bender,该误差可能会进一步减少60%。

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