Data-Driven Synthetic Modeling of Trees

In this paper, we develop a data-driven technique to model trees from a single laser scan. A multi-layer representation of the tree structure is proposed to guide the modeling process. In this process, a marching cylinder algorithm is first developed to construct visible branches from the laser scan data. Three levels of crown feature points are then extracted from the scan data to synthesize three layers of non-visible branches. Based on the hierarchical particle flow technique, the branch synthesis method has the advantage of producing visually convincing tree models that are consistent with scan data. User intervention is extremely limited. The robustness of this technique has been validated on both conifer and broadleaf trees.