ABSTRACT In the field of industrial design, most manufactured objects are designed using 3D CAD (Computer-Aided Design) model. However, the original design may sometimes be lost or not available. A reverse engineering approach is then required to generate a geometric CAD model from 3D point clouds obtained by scanning objects. In this paper, an adaptive process for automatic reconstruction of CAD model from point clouds is proposed. First, the approach extracts primitive shapes from point clouds by RANSAC algorithm, then it analyses deviations of points from the fitted primitive shapes by histograms. For point cloud patches segmented unreasonable, the approach updates parameters of segmentation according to the Gaussian noise and repeats the primitive shape detection process. After certain rounds of iteration, the approach can detect reasonable primitive shapes from point clouds. Then a rule for obtaining CAD models by primitive shape alignment is introduced. The proposed approach is evaluated on datasets provided by the AIM@SHAPE Shape Repository.

中文翻译：

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从点云到CAD模型的逆向工程自适应过程

摘要 在工业设计领域，大多数制造对象都是使用 3D CAD（计算机辅助设计）模型设计的。但是，原始设计有时可能会丢失或不可用。然后需要逆向工程方法从通过扫描对象获得的 3D 点云生成几何 CAD 模型。在本文中，提出了一种从点云自动重建CAD模型的自适应过程。首先，该方法通过RANSAC算法从点云中提取原始形状，然后通过直方图分析点与拟合原始形状的偏差。对于分割不合理的点云块，该方法根据高斯噪声更新分割参数并重复原始形状检测过程。经过几轮迭代后，该方法可以从点云中检测出合理的原始形状。然后介绍了通过原始形状对齐获得CAD模型的规则。所提出的方法是在 AIM@SHAPE 形状存储库提供的数据集上进行评估的。