A 3D terrain meshing method based on discrete point cloud

2017 ◽

Vol XLII-2/W6 ◽

pp. 101-107

Author(s):

T. Fiolka ◽

F. Rouatbi ◽

D. Bender

Keyword(s):

Point Cloud ◽

Ground Plane ◽

Point Clouds ◽

Current Approach ◽

Automated Detection ◽

Lidar System ◽

3D Point Clouds ◽

Terrain Models ◽

3D Terrain ◽

Flight Route

3D terrain models are an important instrument in areas like geology, agriculture and reconnaissance. Using an automated UAS with a line-based LiDAR can create terrain models fast and easily even from large areas. But the resulting point cloud may contain holes and therefore be incomplete. This might happen due to occlusions, a missed flight route due to wind or simply as a result of changes in the ground height which would alter the swath of the LiDAR system. This paper proposes a method to detect holes in 3D point clouds generated during the flight and adjust the course in order to close them. First, a grid-based search for holes in the horizontal ground plane is performed. Then a check for vertical holes mainly created by buildings walls is done. Due to occlusions and steep LiDAR angles, closing the vertical gaps may be difficult or even impossible. Therefore, the current approach deals with holes in the ground plane and only marks the vertical holes in such a way that the operator can decide on further actions regarding them. The aim is to efficiently create point clouds which can be used for the generation of complete 3D terrain models.

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A Complete Method for Reconstructing an Elevation Surface of 3D Point Clouds

REV Journal on Electronics and Communications ◽

10.21553/rev-jec.79 ◽

2015 ◽

Vol 4 (3-4) ◽

Cited By ~ 1

Author(s):

Van Sinh Nguyen ◽

Manh Ha Tran ◽

Ba Cong Nhan

Keyword(s):

Point Cloud ◽

Input Data ◽

Smooth Surface ◽

Point Clouds ◽

Triangular Mesh ◽

Second Step ◽

Discrete Point ◽

The Third ◽

Input Surface ◽

3D Point Clouds

Reconstructing the surface of 3D point clouds is a reconstruction from a cloud of 3D points to a triangular mesh. This process approximates a discrete point cloud by a continuous/smooth surface depending on the input data and the applications of users. In this paper, we propose a complete method to reconstruct an elevation surface from 3D point clouds. The method consists of three steps. In the first step, we triangulate an elevation surface of 3D point cloud structured in a 3D grid. In the second step, we remove the outward triangles to deal with concave regions on the boundary of the triangular mesh. In the third step, we reconstruct this surface by filling the hole of triangular mesh. Our method could process very fast for triangulating the surface, preserve the topology and characteristic of the input surface after reconstruction.

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A Robust Fast Bridging Algorithm for Laser Cutting

10.21203/rs.3.rs-970883/v1 ◽

2021 ◽

Author(s):

Qirui Hu ◽

Zhiwei Lin ◽

Jianzhong Fu

Keyword(s):

Laser Cutting ◽

Point Cloud ◽

Effective Strategy ◽

Discrete Point ◽

Line Segments ◽

Easy Task ◽

Delaunay Triangles ◽

Bridge Length ◽

Cutting Experiments ◽

Different Parts

Abstract Bridging the different parts together is considered a simple but effective strategy to reduce the number of piercing operations during laser cutting. However, fast bridging is never an easy task. In this paper, we present a near-linear bridging algorithm for the input parts with the shortest total bridge length. At first, the input part contours are discretized into a point cloud, then the point cloud is triangulated with the Delaunay standard. The shortest line segments between any two adjacent parts are found in the triangles connecting the two parts. These segments are finally extended into bridges. To solve the problem of the damages to the contour characteristics caused by the bridges, some restrictions are set on the screening of the discrete point cloud and the Delaunay triangles. This algorithm not only ensures the minimum total distance of all bridges, but also avoids the problem of generating bridge loops. Computational experiments show that the proposed bridging algorithm is much faster than that in existing commercial software. The feasibility and superiority of the algorithm are verified by actual lasering cutting experiments.

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