High Accuracy Terrain Reconstruction from Point Clouds Using Implicit Deformable Model

机译：使用隐式可变形模型从点云进行高精度地形重构

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Few previous works have studied the modeling of forest ground surfaces from LiDAR point clouds using implicit functions.is a pioneer in this area. However, by design this approach proposes over-smoothed surfaces, in particular in highly occluded areas, limiting its ability to reconstruct fine-grained terrain surfaces. This paper presents a method designed to finely approximate ground surfaces by relying on deep learning to separate vegetation from potential ground points, filling holes by blending multiple local approximations through the partition of unity principle, then improving the accuracy of the reconstructed surfaces by pushing the surface towards the data points through an iterative convection model.

机译：很少有先前的研究使用隐函数从LiDAR点云研究森林地面的建模。这是该领域的先驱。但是，通过设计，这种方法会产生过度平滑的表面，尤其是在高度遮挡的区域，这限制了其重建细粒度地形表面的能力。本文提出了一种方法，该方法旨在通过深度学习将植被与潜在的地面点分离，通过在统一原则的划分下混合多个局部近似值来填充孔，然后通过推动表面来提高重构表面的精度，从而精确地近似地面通过迭代对流模型处理数据点。

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《International Conference on Computational Science》|2020年|251-265|共15页
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Jules Morel; Alexandra Bac; Takashi Kanai;
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Implicit surface; Deformable model; Deep learning;

机译：隐式表面;可变形模型深度学习;

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1. The vertical accuracy of digital terrain models derived from the close-range photogrammetry point cloud using different methods of interpolation and resolutions [J] . Juraj ?erňava, Franti?ek Chudy, Daniel Tunák, Central European Forestry Journal . 2019,第3a4期

机译：使用不同的插值和分辨率的近距离摄影测量点云衍生的数字地形模型的垂直精度
2. The vertical accuracy of digital terrain models derived from the close-range photogrammetry point cloud using different methods of interpolation and resolutions [J] . Juraj ??er??ava, Franti??ek Chud??, Daniel Tun??k, Lesnicky casopis . 2019,第3a4期

机译：使用不同的插值和分辨率的近距离摄影测量点云衍生的数字地形模型的垂直精度
3. Effects of point cloud density, interpolation method and grid size on derived Digital Terrain Model accuracy at micro topography level [J] . Aguera-Vega F., Aguera-Puntas M., Martinez-Carricondo P., International journal of remote sensing . 2020,第21a22期

机译：点云密度，插值法和电网尺寸对微型地形水平推导数字地形模型精度的影响
4. Generic deformable implicit mesh models for automated reconstruction [C] . Ilic S., Fua P. Higher-Level Knowledge in 3D Modeling and Motion Analysis, 2003. HLK 2003. First IEEE International Workshop on . 2003

机译：用于自动重建的通用可变形隐式网格模型
5. Advances in vehicle-terrain interaction modeling for small, rigid-wheeled vehicles operating on deformable terrain. [D] . Meirion-Griffith, Gareth. 2012

机译：适用于在可变形地形上运行的小型刚性轮式车辆的车地相互作用模型的进展。
6. Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy [O] . Zsuzsanna Szabó, Csaba Albert Tóth, Imre Holb, 2020

机译：航空激光扫描数据作为河流环境中地形建模的来源：地形高度精度的偏差因素
7. Generic Deformable Implicit Mesh Models for Automated Reconstruction [O] . Slobodan Ilic, Pascal Fua 2003

机译：用于自动重建的通用可变形隐式网格模型
8. 4D Reconstructions from Low-Count Spect Data Using Deformable Models with SmoothInterior Intensity Variations [R] . Cunningham, G. S., Lehovich, A. 2000

机译：使用具有平滑内强度变化的可变形模型从低计数光谱数据重建4D

High Accuracy Terrain Reconstruction from Point Clouds Using Implicit Deformable Model

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