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Surface Reconstruction from Fitted Shape Primitives

机译:拟合形状基元的表面重建

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In this paper we address the problem of reconstructing a structurally simple surface representation from point datasets of scanned scenes as they occur for instance in city scanning projects. Such datasets generally suffer from all kinds of scanning artifacts including noise, outliers, holes and irreg-ular/anisotropic sampling. Most common surface reconstruction methods fail due to these shortcomings. We present a robust and efficient method to compute local properties for each data point, use this information to detect simple primitive shapes in the data and describe a novel method to extract and optimize boundary curves on the primitive shapes. Employing the reconstructed boundary curves, we are able to extract a piecewise smooth surface mesh which is mandatory for many further processing applications including visualization. We show the effectiveness of our method with reconstructions of synthetic datasets as well as laser-scanner-acquisitions of indoor and outdoor environments.
机译:在本文中,我们解决了从例如在城市扫描项目中出现的被扫描场景的点数据集重构结构简单的表面表示的问题。这样的数据集通常遭受各种扫描伪像的困扰,包括噪声,离群值,空洞和不规则/各向异性采样。由于这些缺点,最常见的表面重建方法失败了。我们提出了一种强大而有效的方法来计算每个数据点的局部属性,使用此信息来检测数据中的简单原始形状,并描述一种新颖的方法来提取和优化原始形状上的边界曲线。利用重构的边界曲线,我们能够提取出分段光滑的表面网格,这对于包括可视化在内的许多进一步处理应用是必不可少的。我们通过合成数据集的重建以及室内和室外环境的激光扫描仪的购置展示了我们方法的有效性。

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