Extraction method of single tree skeleton points based on SX10 point cloud

doi:10.13474/j.cnki.11-2246.2020.0100

Abstract

Abstract: Skeleton point is the basis of geometric model reconstruction of single tree. This paper combines three methods of level set, clustering and graph theory to extract skeleton points of single tree by using LIMSVP and Trimble SX10 to obtain point cloud data of simulated and measured single tree, and realize the skeleton point extraction of single tree. The simulation data is used for method implementation and the measured data is used for verification. In order to solve the problem of missing point cloud of single tree, three methods of level set, clustering and graph theory are reused to obtain more complete skeleton point of single tree. The results show that the method of extracting skeleton points of single tree is feasible.

Key words: point cloud, skeleton, neighborhood map, mapping, ILMSVP, Trimble SX10

CLC Number:

P237

LIN Zhidong, HE Yuanrong, ZHUANG Yinguo. Extraction method of single tree skeleton points based on SX10 point cloud[J]. Bulletin of Surveying and Mapping, 2020, 0(3): 160-162.

References

[1] 王晓辉. 基于地面激光雷达点云的单树三维几何建模研究[D]. 福州: 福州大学, 2014.
[2] VERROUST A, LAZARUS F. Extracting skeletal curves from 3D scattered data[J]. Visual Computer, 2000, 16(1):15-25.
[3] CÔTÉ J F, WIDLOWSKI J L, FOURNIER R A, et al. 2009. The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial LiDAR[J]. Remote Sensing of Environment, 113(5): 1067-1078.
[4] CÔTÉ J F, FOURNIER R A, EGLI R, et al. 2011. An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR[J]. Environmental Modelling & Software, 26(6): 761-777.
[5] DELAGRANGE S, ROCHON P. Reconstruction and analysis of a deciduous sapling using digital photographs orterrestrial-LiDAR technology[J]. Annual Botany, 2011, 108(6): 991-1000.
[6] 王向玉, 谢东辉, 汪艳,等. 基于地面激光雷达点云数据的单木三维重建[J]. 遥感技术与应用, 2015, 30(3):455-460.
[7] 王向玉. 基于单木精细测量的森林三维场景构建[D]. 北京: 北京师范大学, 2015.
[8] XU H, GOSSETT N, CHEN B. Knowledge and heuristic-based modeling of laser-scanned trees[J]. ACM Transaction on Graphics, 2007, 26(4):19.
[9] YAN D, WINTZ J, MOURRAIN B, et al. Efficient and robust reconstruction of botanical branching structure from laser scanned points[C]//IEEE International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics 2009). Huangshan, China: [s.n.], 2009.
[10] BUCKSCH A, LINDENBERGH R. CAMPINO—A skeletionization method for point cloud processing[J]. ISPRS journal of photogrammetry and remote sensing, 2008, 63(1):115-127.
[11] EUROPEAN COMMISSION. Radiation transfer model intercomparison(RAMI-IV)[EB/OL]. (2012-04-04)[2019-12-20]. http://rami-benchmark.jrc.ec.europa.eu/HTML/RAMI-IV-RAMI-IV.php.

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