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Contour-Based Surface Reconstruction using MPU Implicit Models.
Graphical Models ( IF 1.7 ) Pub Date : 2007-03-01 , DOI: 10.1016/j.gmod.2006.09.007
Ilya Braude 1 , Jeffrey Marker , Ken Museth , Jonathan Nissanov , David Breen
Affiliation  

This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that make up the contours as points in ℝ(3) and employs Multi-level Partition of Unity (MPU) implicit models to create a surface that approximately fits to the 3D points. Since MPU implicit models additionally require surface normal information at each point, an algorithm that estimates normals from the contour data is also described. Contour data frequently contains noise from the scanning and delineation process. MPU implicit models provide a superior approach to the problem of contour-based surface reconstruction, especially in the presence of noise, because they are based on adaptive implicit functions that locally approximate the points within a controllable error bound. We demonstrate the effectiveness of our technique with a number of example datasets, providing images and error statistics generated from our results.

中文翻译:

使用 MPU 隐式模型的基于轮廓的表面重建。

本文提出了一种从一组 2D 轮廓创建平滑、封闭表面的技术,这些 2D 轮廓是从 3D 扫描中提取的。该技术将构成轮廓的像素解释为 ℝ(3) 中的点,并采用多级统一分区 (MPU) 隐式模型来创建近似拟合 3D 点的表面。由于 MPU 隐式模型额外需要每个点的表面法线信息,因此还描述了一种从轮廓数据估计法线的算法。轮廓数据经常包含来自扫描和描绘过程的噪声。MPU 隐式模型为解决基于轮廓的表面重建问题提供了一种优越的方法,尤其是在存在噪声的情况下,因为它们基于自适应隐式函数,在可控误差范围内局部逼近点。
更新日期:2019-11-01
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