大规模点云直线段的提取

Line Segment Extraction from Large-Scale Point Clouds

三维直线段作为最常见的基元,在人工场景的矢量重建中发挥着重要作用。本文提出了一种从大规模点云中三维直线段提取的方法。该方法首先通过区域增长和区域合并提取了三维投影平面,然后将其投影成二维图像,最后将投影图像中提取的二维直线段反投影到三维空间得到了三维直线段。大规模户外场景的点云数据集实验表明,所提出的方法可精准地提取场景中的直线特征线段,同时过滤掉大部分的噪声,从而能够提取更完整的直线段。与人工标注的真值直线段相比( : 0.5, 0.5)相比,本文提出的方法提取的完成率和准确率平均达到83%,而且平均处理速度为每秒27,000点。

As the most common primitives, line segments play an essential role in the vectorized reconstruction of artificial scenes. In this paper, a method is proposed to extract line segments from large-scale point clouds. This method firstly extracts the 3D projection plane through region growing and region merging, then projects it to 2D to form an image, and finally back-projects the 2D line segment extracted from the projected image to 3D to obtain a 3D line segment. Experiments on point clouds datasets of large-scale outdoor scenes show that the proposed method can accurately extract the linear feature line segments representing the scene, filter out major nosie, and extract more complete line segments. The Completeness and Correctness of the line segments extraction results reach 83% on average compared with manual labeled ground truth ( : 0.5, 0.5), at an average processing speed of 27,000 points per second.