Targetless Coregistration of Terrestrial Laser Scanning Point Clouds Using a Multi Surrounding Scan Image-Based Technique

B. Alsadik
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Abstract

The coregistration of terrestrial laser point clouds is widely investigated where different techniques are presented to solve this problem. The techniques are divided either as target-based or targetless approaches for coarse and fine coregistration. The targetless approach is more challenging since no physical reference targets are placed in the field during the scanning. Mainly, targetless methods are image-based and they are applied through projecting the point clouds back to the scanning stations. The projected 360 point cloud images are normally in the form of panoramic images utilizing either intensity or RGB values, and an image matching is followed to align the scan stations together. However, the point cloud coregistration is still a challenge since ICP like methods are applicable for fine registration. Furthermore, image-based approaches are restricted when there is: a limited overlap between point clouds, no RGB data accompanied to intensity values, and unstructured scanned objects in the point clouds. Therefore, we present in this paper the concept of a multi surrounding scan MSS image-based approach to overcome the difficulty to register point clouds in challenging cases. The multi surrounding scan approach means to create multi-perspective images per laser scan point cloud. These multi-perspective images will offer different viewpoints per scan station to overcome the viewpoint distortion that causes the failure of the image matching in challenging situations. Two experimental tests are applied using point clouds collected in Enschede city and the published 3D toolkit data set in Bremen city. The experiments showed a successful coregistration approach even in challenging settings with different constellations.
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基于多周围扫描图像技术的地面激光扫描点云无目标共配准
地面激光点云的共配准得到了广泛的研究,并提出了不同的技术来解决这一问题。这些技术分为基于目标和无目标的粗配准方法和精细配准方法。无目标方法更具挑战性,因为在扫描过程中没有放置物理参考目标。无目标方法主要是基于图像的,通过将点云投影回扫描站来应用。投影的360点云图像通常是利用强度或RGB值的全景图像的形式,并遵循图像匹配将扫描站对齐在一起。然而,点云共配准仍然是一个挑战,因为类似ICP的方法适用于精细配准。此外,当点云之间重叠有限,没有RGB数据伴随强度值,并且点云中存在非结构化扫描对象时,基于图像的方法受到限制。因此,本文提出了一种基于多周围扫描MSS图像的方法的概念,以克服在具有挑战性的情况下点云配准的困难。多周围扫描方法是指在每个激光扫描点云上创建多视角图像。这些多视角图像将为每个扫描站提供不同的视点,以克服在具有挑战性的情况下导致图像匹配失败的视点失真。使用在恩斯赫德市收集的点云和在不来梅市公布的3D工具包数据集进行了两次实验测试。实验表明,即使在具有不同星座的挑战性环境中,共配准方法也是成功的。
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