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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Facet Segmentation-Based Line Segment Extraction for Large-Scale Point Clouds
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Facet Segmentation-Based Line Segment Extraction for Large-Scale Point Clouds

机译：基于小平面分割的大规模点云线段提取

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摘要

As one of the most common features in the man-made environments, straight lines play an important role in many applications. In this paper, we present a new framework to extract line segments from large-scale point clouds. The proposed method is fast to produce results, easy for implementation and understanding, and suitable for various point cloud data. The key idea is to segment the input point cloud into a collection of facets efficiently. These facets provide sufficient information for determining linear features in the local planar region and make line segment extraction become relatively convenient. Moreover, we introduce the concept “number of false alarms” into 3-D point cloud context to filter the false positive line segment detections. We test our approach on various types of point clouds acquired from different ways. We also compared the proposed method with several other methods and provide both quantitative and visual comparison results. The experimental results show that our algorithm is efficient and effective, and produce more accurate and complete line segments than the comparative methods. To further verify the accuracy of the line segments extracted by the proposed method, we also present a line-based registration framework, which employs these line segments on point clouds registration.
机译：作为人为环境中最常见的功能之一，直线在许多应用中起着重要的作用。在本文中，我们提出了一个从大型点云中提取线段的新框架。所提出的方法快速产生结果，易于实现和理解，并且适合于各种点云数据。关键思想是将输入点云有效地分割成一组构面。这些方面为确定局部平面区域中的线性特征提供了足够的信息，并使线段提取变得相对方便。此外，我们将“错误警报数”概念引入3-D点云上下文，以过滤错误的正线段检测。我们对通过不同方式获取的各种类型的点云测试了我们的方法。我们还将提出的方法与其他几种方法进行了比较，并提供了定量和视觉比较结果。实验结果表明，与比较方法相比，我们的算法是有效的，并且可以产生更准确，更完整的线段。为了进一步验证所提方法提取的线段的准确性，我们还提出了一种基于线的配准框架，该框架在点云配准上采用了这些线段。

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