Three Dimensional Tree Modeling Based on the Skeleton Path Optimization and Geometrical Shapes
DOI:
https://doi.org/10.9781/ijimai.2024.10.003Keywords:
Automatic Tree Modeling, Extraction, Geometric Cones, Optimization, Point CloudAbstract
Nowadays, the 3D individual tree reconstruction has played a significant role in the phenotypic study of trees. This paper proposes a new automatic method for extracting skeletons of individual trees and reconstructing 3D models. Firstly, the Euclidean clustering is performed to obtain center points of candidate branch regions. Then, the initial skeletons of LiDAR point clouds are obtained by slicing clusters in three dimensions. Secondly, skeleton points are completed by the proposed branch tracking. Then, the radius of the branches is accurately estimated from the branches. Thirdly, optimal points are interpolated in appropriate directions to refine skeletons of individual trees. Then, the Laplacian algorithm is conducted for smoothing branches. After that, optimal geometric shapes are formulated to reconstruct the final 3D tree models. Experimental results show that the average accuracy of our individual tree models is up to 97.49%, which shows a promising algorithm in 3D tree reconstructions.
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C. Sun, C. Huang, H. Zhang, B. Chen, F. An, L. Wang, and T. Yun, “Individual Tree Crown Segmentation and Crown Width Extraction From a Heightmap Derived From Aerial Laser Scanning Data Using a Deep Learning Framework” Frontiers in plant science, vol. 13, 2022, doi: https://doi.org/10.3389/fpls.2022.914974
M. Schmitt, M. Shahzad, and X.X. Zhu, “Reconstruction of individual trees from multi-aspect TomoSAR data,” Remote Sensing of Environment, vol. 165, pp. 175-185, 2015.
G.Z. He, “The Trees Skeleton Extraction Based on Point Cloud Contraction,” Applied Mechanics and Materials, vol. 475, pp. 355-360, 2014.
E. Bournez, T. Landes, M. Saudreau, P. Kastendeuch, and G. Najja, “From TLS point clouds to 3D models of trees: a comparison of existing algorithms for 3D tree reconstruction,” in 3d Virtual Reconstruction and Visualization of Complex Architectures, vol. 42, no. 2, pp. 113-120, 2017.
R. Maalek, D.D. Lichti, R. Walker, A. Bhavnani, and J.Y. Ruwanpura, “Extraction of pipes and flanges from point clouds for automated verification of pre-fabricated modules in oil and gas refinery projects,” Automation in Construction, vol. 103, pp. 150-167, 2019.
S. Xu, X. Li, J.Y. Yun, and S.S. Xu, “An Effectively Dynamic Path Optimization Approach for the Tree Skeleton Extraction from Portable Laser Scanning Point Clouds,” Remote Sensing, vol. 14, no. 1, pp. 94, 2022.
A. Verroust, and F. Lazarus, “Extracting skeletal curves from 3D scattered data,” in Proceedings Shape Modeling International ‘99. International Conference on Shape Modeling and Applications, Aizu-Wakamatsu, Japan, pp. 194-201, 1999, doi: 10.1109/SMA.1999.749340.
H. Xu, N. Gossett, and B. Chen, “Knowledge and heuristic-based modeling of laser-scanned trees,” ACM Transactions on Graphics (TOG), vol. 26, no. 4, 2007, doi: 10.1145/1289603.1289610.
Y. Livny, F. Yan, M. Olson, B. Chen, H Zhang, J El-Sana, “Automatic reconstruction of tree skeletal structures from point clouds,” in ACM SIGGRAPH Asia 2010 papers (SIGGRAPH ASIA ‘10). Association for Computing Machinery, New York, NY, USA, 2010, Article 151, pp. 1–8. https://doi.org/10.1145/1866158.1866177.
N. Pfeifer, B. Gorte, and D. Winterhalder, “Automatic reconstruction of single trees from terrestrial laser scanner data,” in Proceedings of the 20th ISPRS Congress, Istanbul, Turkey, 2004, vol. 35, pp. 114-119, 2004.
J. Li, H. Wu, Z. Xiao, and H. Lu, “3D modeling of laser-scanned trees based on skeleton refined extraction,” International Journal of Applied Earth Observation and Geoinformation, vol. 112, pp. 102694, 2022, doi: 10.1016/j.jag.2022.102943.
A. Jiang, J. Liu, J. Zhou, and M. Zhang, “Skeleton extraction from point clouds of trees with complex branches via graph contraction,” The Visual Computer, vol. 37, pp. 2235–2251, 2021, doi: 10.1007/s00371-020-01983-6.
Q. Li, X. Li, Y. Tong, X. Liu, “Street tree crown detection with mobile laser scanning data using a grid index and local features,” PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, vol. 90, no. 3, pp. 305-317, 2022.
S. Xu, S.S. Xu, N. Ye, and F. Zhu, “Automatic extraction of street trees’ nonphotosynthetic components from MLS data,” International Journal of Applied Earth Observation and Geoinformation, vol. 69, pp. 64-77, 2018.
X.D. Hu, C.H. Hu, J.G Han, H. Sun, and R. Wang, “Point cloud segmentation for an individual tree combining improved point transformer and hierarchical clustering,” Journal of Applied Remote Sensing, 2023.
Y.F. Xu, C.H. Hu and Y.N. Xie, “An improved space colonization algorithm with DBSCAN clustering for a single tree skeleton extraction,” International Journal of Remote Sensing, vol. 43, pp. 3692-3713, 2022.
B. Zhang, X.J. Wang, X.Y. Yuan, F An, H.Q. Zhang, L Zhou, J Shi, and T Yun, “Simulating Wind Disturbances over Rubber Trees with Phenotypic Trait Analysis Using Terrestrial Laser Scanning,” Forests, vol. 13, no. 8, pp. 1298, 2022.
X. Xue, S. Jin, F. An, H. Zhang, J. Fan, M.P. Eichhorn, C. Jin, B. Chen, L. Jiang, and T. Yun, “Shortwave Radiation Calculation for Forest Plots Using Airborne LiDAR Data and Computer Graphics,” Plant Phenomics, 2022.
X. Li, X. Zhou, and S. Xu, “Individual Tree Reconstruction Based on Circular Truncated Cones From Portable LiDAR Scanner Data,” IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, 2022.
P. Raumonen, M. Kaasalainen, M. Åkerblom, S Kaasalainen, H. Kaartinen, M. Vastaranta, M. Holopainen, M. Disney, and P. Lewis, “Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data,” Remote Sensing, vol. 5, 2013
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