We present a semi-automatic and efficient method for producing full polygonal models of range scanned trees, which are initially represented as sparse point clouds. First, a skeleton of the trunk and main branches of the tree is produced based on the scanned point clouds. Due to the unavoidable incompleteness of the point clouds produced by range scans of trees, steps are taken to synthesize additional branches to produce plausible support for the tree crown. Appropriate dimensions for each branch section are estimated using allometric theory. Using this information, a mesh is produced around the full skeleton. Finally, leaves are positioned, oriented and connected to nearby branches. Our process requires only minimal user interaction, and the full process including scanning and modeling can be completed within minutes.

We present a GPU supported interactive non-photorealistic rendering system, INSPIRE, which performs feature extraction in both image space, on intermediately rendered images, and object space, on models of various representations, e.g., point, polygon, or hybrid models, without needing connectivity information. INSPIRE obtains interactive NPR rendering with most styles of existing NPR systems, but offers more flexibility on model representations and compromises little on rendering speed.