KEYWORDS: LIDAR, Data acquisition, 3D acquisition, 3D modeling, Data modeling, Binary data, Algorithm development, Data processing, Agriculture, Reconstruction algorithms
As the 3D point-cloud data increase greatly with the development of data acquisition technology, it is an important prerequisite to establish an efficient index constructing and neighbor searching algorithm for point-cloud in data processing. In this paper, an efficient algorithm of index constructing and neighbor searching for 3D LiDAR data was proposed based on the combination of 3D grid, linear octree and Hash table. An experiment was conducted about the 3D LiDAR data and the result shows that the proposed method has higher efficiency of data index constructing and neighbor searching for 3D point-cloud acquired by mobile LiDAR.
KEYWORDS: LIDAR, Data acquisition, 3D acquisition, 3D modeling, Data modeling, Binary data, Algorithm development, Data processing, Agriculture, Reconstruction algorithms
As the 3D point-cloud data increase greatly with the development of data acquisition technology, it is an important prerequisite to establish an efficient index constructing and neighbor searching algorithm for point-cloud in data processing. In this paper, an efficient algorithm of index constructing and neighbor searching for 3D LiDAR data was proposed based on the combination of 3D grid, linear octree and Hash table. An experiment was conducted about the 3D LiDAR data and the result shows that the proposed method has higher efficiency of data index constructing and neighbor searching for 3D point-cloud acquired by mobile LiDAR.
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