> While the above equation, dubbed the "superformula" by Gielis (2003), is clearly capable of describing a number of diverse biological shapes having a variety of symmetries, it seems unlikely that this formula has any particularly fundamental biological significance (Peterson 2002, Whitfield 2003) beyond as a possibly convenient parametrization. [1]
I'm not a huge fan of these random parametrizations; overall, it seems like they have no physical significance (yay! it can describe a bunch of things! I can do that anyways by picking a linear space with enough dimensions or a nice non-linear kernel and projecting into the first few principal components, and best of all, it's going to be fit directly to my problem). I'd like to be enlightened as to why this is such a big deal and why anyone would do this instead of parametrization of meshes for procedural generation? It seems a few comments here are referencing NMS, hence the question.
I'm not a huge fan of these random parametrizations; overall, it seems like they have no physical significance (yay! it can describe a bunch of things! I can do that anyways by picking a linear space with enough dimensions or a nice non-linear kernel and projecting into the first few principal components, and best of all, it's going to be fit directly to my problem). I'd like to be enlightened as to why this is such a big deal and why anyone would do this instead of parametrization of meshes for procedural generation? It seems a few comments here are referencing NMS, hence the question.
[1] http://mathworld.wolfram.com/Superellipse.html