[legel]

As someone who has invested a career into 3D modeling of plants, particularly of real plants from 3D scanner data, I really don't find value in this work, scientifically. It surely is fun and useful for artistic purposes, where the only evaluation is from a human eye. But when you actually compare the structures of the algorithms presented here to the real curves and topologies of any living plant, you find that they are missing a tremendous amount of detail. From a machine learning perspective, e.g., it would be very hard to "fit" these models to actual data. This is because these algorithms and data structures assume far too much homogeneity in the basic structures of a given species, particularly that these structures be repeated with only simple rotations and permutations. In fact, when you look closely at leaves and flowers and roots and stems of a plant, there is more and more detail; just like any living system, this is because plants are very active on a microbiological level that causes a level of microscopic entropy well beyond that of any single Bezier curve (or whatever). So for those who really do love the beauty of plants, and who really do want to model them and therefore be able to propagate their forms in the digital space, I would suggest looking elsewhere, and in particular seeking ways that are more data-driven to model plants. As it stands in this work, there are no objective functions or optimizations, this is just purely art that is disconnected from the reality in myriad immeasurable dimensions.

[jmmcd]

Well, all models are wrong, but some are useful. I think L-systems and similar are useful for giving a basic conceptual understanding of branching and recursive processes which organisms do use, even if reality is more complex.

[tedd4u]

Can you suggest some other books / papers / articles?