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Multi-level height maps-based registration method for sparse LiDAR point clouds in an urban scene

机译：城市场景中稀疏激光雷亚云稀疏基于高度地图的基于多级高度地图

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摘要

The LiDAR sensor has been widely used for reconstruction in urban scenes. However, the current registration method makes it difficult to find stable 3D point correspondences from sparse and low overlapping LiDAR point clouds. In the urban situation, most of the LiDAR point clouds have a common flat ground. Therefore, we propose a novel, to the best of our knowledge, multi-level height (MH) maps-based coarse registration method. It requires that source and target point clouds have a common flat ground, which is easily satisfied for LiDAR point clouds in urban scenes. With MH maps, 3D registration is simplified as 2D registration, increasing the speed of registration. Robust correspondences are extracted in MH maps with different height intervals and statistic height information, improving the registration accuracy. The solid-state LiDAR Livox Mid-100 and mechanical LiDAR Velodyne HDL-64E are used in real-data and dataset experiments, respectively. Verification results demonstrate that our method is stable and outperforms state-of-the-art coarse registration methods for the sparse case. Runtime analysis shows that our method is faster than these methods, for it is non-iterative. Furthermore, our method can be extended for the unordered multi-view point clouds. (C) 2021 Optical Society of America
机译：激光雷达传感器已广泛用于城市场景的重建。然而，目前的配准方法难以从稀疏和低重叠的激光雷达点云中找到稳定的三维点对应。在城市环境中，大多数激光雷达点云都有一个共同的平坦地面。因此，我们提出了一种基于多级高度（MH）映射的粗配准方法。它要求源点云和目标点云有一个共同的平坦地面，这对于城市场景中的激光雷达点云来说很容易满足。使用MH地图，3D注册简化为2D注册，提高了注册速度。在不同高度间隔和统计高度信息的MH地图中提取鲁棒对应，提高了配准精度。固体激光雷达Livox Mid-100和机械激光雷达Velodyne HDL-64E分别用于实际数据和数据集实验。验证结果表明，对于稀疏情况，我们的方法是稳定的，并且优于现有的粗配准方法。运行时分析表明，我们的方法比这些方法更快，因为它是非迭代的。此外，我们的方法还可以推广到无序的多视点云。（2021）美国光学学会

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  • 来源
    《Applied optics》 |2021年第14期|共11页
  • 作者

    Fang Bin; Ma Jie; An Pei; Wang Zhao; Zhang Jun; Yu Kun;

  • 作者单位

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol HUST Sch Artificial Intelligence &

    Automat Wuhan 430074 Hubei Peoples R China;

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  • 正文语种 eng
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