Feature lines are important geometric cues in characterizing the structure of a CAD model. Despite great progress in both explicit reconstruction and implicit reconstruction, it remains a challenging task to reconstruct a polygonal surface equipped with feature lines, especially when the input point cloud is noisy and lacks faithful normal vectors. In this paper, we develop a multistage algorithm, named RFEPS, to address this challenge. The key steps include (1)denoising the point cloud based on the assumption of local planarity, (2)identifying the feature-line zone by optimization of discrete optimal transport, (3)augmenting the point set so that sufficiently many additional points are generated on potential geometry edges, and (4) generating a polygonal surface that interpolates the augmented point set based on restricted power diagram. We demonstrate through extensive experiments that RFEPS, benefiting from the edge-point augmentation and the feature-preserving explicit reconstruction, outperforms state-of-the-art methods in terms of the reconstruction quality, especially in terms of the ability to reconstruct missing feature lines.
翻译:CAD模型结构特征的特征线是重要的几何标志。 尽管在明确的重建和隐含重建方面都取得了很大进展,但重建一个配有特征线的多边形表面仍是一项艰巨的任务,特别是当输入点云是吵闹的,缺乏忠实的正常矢量时。在本文中,我们开发了一个名为RFEPS的多阶段算法来应对这一挑战。关键步骤包括:(1) 假设地方规划性,对点云进行分辨;(2) 通过优化离散最佳运输,确定地线区;(3) 提高设定点,以便在潜在的几何边缘产生足够多的额外点;(4) 生成一个多边形表面,以内插基于限制电图的扩大点。我们通过广泛的实验证明,RFEPS从边点增强和特征保留明显重建中受益,在重建质量方面超越了最新的方法,特别是在重建缺失的地貌线的能力方面。