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Automated registration of dense terrestrial laser-scanning point clouds using curves

机译:使用曲线自动记录密集的地面激光扫描点云

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摘要

This paper proposes an automatic method for registering terrestrial laser scans in terms of robustness and accuracy. The proposed method uses spatial curves as matching primitives to overcome the limitations of registration methods based on points, lines, or patches as primitives. These methods often have difficulty finding correspondences between the scanned point clouds of freeform surfaces (e.g., statues, cultural heritage). The proposed method first clusters visually prominent points selected according to their associated geometric curvatures to extract crest lines which describe the shape characteristics of point clouds. Second, a deformation energy model is proposed to measure the shape similarity of these crest lines to select the correct matching-curve pairs. Based on these pairs, good initial orientation parameters can be obtained, resulting in fine registration. Experiments were undertaken to evaluate the robustness and accuracy of the proposed method, demonstrating a reliable and stable solution for accurately registering complex scenes without good initial alignment.
机译:本文就鲁棒性和准确性提出了一种自动注册地面激光扫描的方法。所提出的方法使用空间曲线作为匹配基元来克服基于点,线或面片作为基元的配准方法的局限性。这些方法通常难以找到自由曲面(例如雕像,文化遗产)的扫描点云之间的对应关系。所提出的方法首先将根据其相关的几何曲率选择的视觉突出点进行聚类,以提取描述点云形状特征的波峰线。其次,提出了一个变形能量模型来测量这些波峰线的形状相似度,以选择正确的匹配曲线对。基于这些对,可以获得良好的初始取向参数,从而导致良好的配准。进行了实验,以评估所提出方法的鲁棒性和准确性,证明了一种可靠且稳定的解决方案,可在没有良好初始对准的情况下准确地记录复杂场景。

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