Synthetic tree models from iterated discrete graphs

We present a method to generate models for trees in which we first create a weighted graph, then places endpoints and root point and plan least-cost paths from endpoints to the root point. The collection of resulting paths form a branching structure. We create a hierarchical tree structure by placing subgraphs around each endpoint and beginning again through some number of iterations. Powerful control over the global shape of the resulting tree is exerted by the shape of the initial graph, allowing users to create desired variations; more subtle variations can be accomplished by modifying parameters of the graph and subgraph creation processes and by changing the endpoint distribution mechanisms. The method is capable of matching a desired target structure with a little manual effort, and can easily generate a large group of slightly different models under the same parameter settings. The final trees are both intricate and convincingly realistic in appearance.