Tree Reconstruction Using Topology Optimisation

Generating accurate digital tree models from scanned environments is invaluable for forestry, agriculture, and other outdoor industries in tasks such as identifying fall hazards, estimating trees’ biomass calculating traversability. Existing methods reconstruction rely on sparse feature identification to segment a forest into individual trees generate branch structure graph, limiting their application easily separable uniform forests. However, the natural world messy place which present with significant heterogeneity are frequently encroached upon by surrounding environment. We general method extracting of point cloud data, estimates adapting structural topology optimisation find optimal material distribution interpolate input data. results this over wide variety scans, discuss benefits drawbacks novel approach reconstruction. Our generates detailed structures, mean Surface Error (SE) 15 cm 13 diverse datasets.