A Registration Method Based on Planar Features Between BIM Model and Point Cloud

Qiwen Wu, Xi Zhao
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Abstract

In the digitization process of the construction industry, it is frequently necessary to use BIM as a digital model carrier, and the registration between BIM and point cloud is a crucial step in BIM applications. Most existing 3D registration methods, such as the ICP algorithm, are capable of aligning point clouds. However, these classical methods are subject to the influence of numerous points contained within the point cloud, relying heavily on point-to-point correlations. Consequently, it is challenging to extend these algorithms to register with other forms of spatial information, such as BIM models, beyond the point cloud. Considering that planes are basic geometric elements in building BIM models, this paper proposes a novel method for aligning BIM models with point clouds by matching planar features. The method extracts planes from point clouds using an enhanced region growing algorithm, directly parsing the planar geometric information from BIM in IFC format. After completing the matching of plane groups, the optimal solution is calculated using a weighted least squares method. The experimental results indicate that the proposed method can achieve successful registration between the BIM model and point cloud, with a lower RMSE of 5.73mm compared to the registration method using RANSAC+ICP on the same dataset.
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基于平面特征的 BIM 模型与点云注册方法
在建筑行业的数字化过程中,经常需要使用 BIM 作为数字模型载体,而 BIM 与点云之间的注册是 BIM 应用的关键步骤。现有的大多数三维注册方法(如 ICP 算法)都能对齐点云。但是,这些经典方法受点云中众多点的影响,在很大程度上依赖于点对点的相关性。因此,要将这些算法扩展到与点云之外的其他形式的空间信息(如 BIM 模型)进行注册,具有很大的挑战性。考虑到平面是建筑 BIM 模型中的基本几何元素,本文提出了一种通过匹配平面特征使 BIM 模型与点云对齐的新方法。该方法使用增强型区域生长算法从点云中提取平面,直接解析 IFC 格式 BIM 中的平面几何信息。完成平面组匹配后,使用加权最小二乘法计算出最优解。实验结果表明,在相同的数据集上,与使用 RANSAC+ICP 的注册方法相比,所提出的方法可以实现 BIM 模型和点云之间的成功注册,RMSE 值低至 5.73mm。
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