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H. Shaojun, M. Wimmer et al.:
"Efficient Tree Modeling from Airborne LiDAR Point Clouds";
Computers & Graphics (eingeladen), 67 (2017), 67; S. 1 - 13.

Modeling real-world trees is important in many application areas, including computer graphics, botany and forestry. An example of a modeling method is reconstruction from light detection and ranging (LiDAR) scans. In contrast to terrestrial LiDAR systems, airborne LiDAR systems - even current high-resolution systems - capture only very few samples on tree branches, which makes the reconstruction of trees from airborne LiDAR a challenging task. In this paper, we present a new method to model plausible trees with fine details from airborne LiDAR point clouds. To reconstruct tree models, first, we use a normalized cut method to segment an individual tree point cloud. Then, trunk points are added to supplement the incomplete point cloud, and a connected graph is constructed by searching sufficient nearest neighbors for each point. Based on the observation of real-world trees, a direction field is created to restrict branch directions. Then, branch skeletons are constructed using a bottom-up greedy algorithm with a priority queue, and leaves are arranged according to phyllotaxis. We demonstrate our method on a variety of examples and show that it can generate a plausible tree model in less than one second, in addition to preserving features of the original point cloud.

tree modeling, LIDAR, point clouds

http://dx.doi.org/10.1016/j.cag.2017.04.004

http://publik.tuwien.ac.at/files/publik_261768.pdf