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Sharpen Bend: Recovering curved edges in triangle meshes produced by feature-insensitive sampling

机译:锐化和弯曲:恢复由特征不敏感的采样产生的三角形网格中的弯曲边缘

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摘要

Various 3D acquisition, analysis, visualization and compression approaches sample surfaces of 3D shapes in a uniform fashion, without any attempt to align the samples with the sharp edges and corners of the original shape. Consequently, the interpolating triangle meshes chamfer these sharp features and thus exhibit a relatively large error in their vicinity. We introduce here two new filters that restore a large fraction of the straight or curved sharp edges missed by feature-insensitive sampling processes: (1) EdgeSharpener restores automatically the sharp edges by identifying and splitting the chamfer edges and by forcing the new vertices to lie on intersections of planes extending the smooth surfaces incident upon these chamfers and (2) Bender subdivides the resulting triangle mesh using a combination of the Butterfly subdivision scheme, for the smooth portion of the mesh, with a four-point subdivision scheme, for the sharp edges, in order to preserve the sharpness of the recovered sharp edges while bending their polyline approximations into smooth curves. This combined post-processing (named Sharpen&Bend) significantly reduces the error produced by feature-insensitive sampling processes. For example, we have observed that the L? error introduced by the SwingWrapper remeshing-based compressor can often be reduced down to a fifth by executing EdgeSharpener alone after decompression, with no additional information. For meshes produced by retiling shapes with curved edges, this error may be further reduced by two thirds if we follow the EdgeSharpening phase by Bender. Thus the combined Sharpen&Bend process takes a triangle mesh produced by a feature-insensitive sampling of a curved shape with sharp curved features and automatically refines the mesh to produce a more accurate approximation of the initial shape.
机译:各种3D采集,分析,可视化和压缩均以统一的方式处理3D形状的样本表面,而无需尝试将样本与原始形状的尖锐边缘和角对齐。因此,内插三角形网格对这些尖锐特征进行倒角,因此在其附近显示出较大的误差。我们在这里介绍了两个新的滤镜,它们可以恢复特征不敏感的采样过程遗漏的大部分笔直或弯曲的锐边:(1)EdgeSharpener通过识别和分割倒角边缘并迫使新的顶点平躺来自动恢复锐利的边缘(2)Bender使用Butterfly细分方案(针对网格的平滑部分)与四点细分方案(针对锐利)的组合,将生成的三角形网格细分为在这些倒角上入射的光滑平面的交点上边缘,以保持恢复的锐利边缘的清晰度,同时将折线近似折弯为平滑曲线。这种组合的后处理(称为Sharpen&Bend)可大大减少因特征不敏感的采样过程而产生的错误。例如,我们观察到L?通过SwingWrapper基于重网格的压缩器引入的错误通常可以通过解压缩后仅执行EdgeSharpener来减少至五分之一,而无需任何其他信息。对于通过平铺具有弯曲边缘的形状而生成的网格,如果我们按照Bender的EdgeSharpening阶段进行操作,则此错误可能会进一步减少三分之二。因此,组合的Sharpen&Bend过程采用由特征不敏感的具有尖锐弯曲特征的弯曲形状采样产生的三角形网格,并自动精炼网格以产生更精确的初始形状近似值。

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