generative modeling for Rhino
Metaballs are contours of a 3D scalar field. As an alternative to the typical marching cubes I am trying a force driven approach.
We can differentiate the function for the scalar field to get the gradient vector field, which can be used to push the particles towards a particular threshold value. The particles also repel each other, causing them to distribute evenly across the implicit surface. The particles are then connected according to proximity, the triangles in this graph are found and a mesh is drawn (Still a few issues with this step).
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my graduation project use metaball, i make surface by create point (divide curve x,y,z axis) and the mesh result was not good.I think your way to create mesh surface so great. so, could you share this definition? my email: dongvietngocbao@gmail.com. thanks !
Comment by Hrvoje Petrovic on October 10, 2011 at 1:25am Great!
Jacek - It's certainly faster than my attempt at MC. It still takes a bit of tweaking to get decent particle spacing, but I think potentially this could be pretty fast.
I can't take credit for coming up with the idea of this approach - the first place I think I saw it was this paper by Heckbert and Witkin:
http://www-2.cs.cmu.edu/~aw/pdf/particles-reprint.pdf
some other references here:
http://http.developer.nvidia.com/GPUGems3/gpugems3_ch07.html
http://zurich.disneyresearch.com/~wjarosz/publications/particles.pdf
http://www.cs.utah.edu/~miriah/publications/particle_sampling.pdf
Comment by Pieter Segeren on October 8, 2011 at 1:39pm Way cool! Even wíth the gaps for now.
Comment by Daniel Kautz on October 8, 2011 at 12:48pm Great idea
Comment by Astrid G on October 8, 2011 at 11:52am Amazing!
Comment by Andy Payne on October 8, 2011 at 11:18am Very nice!
Comment by Jacek Jaskólski on October 8, 2011 at 9:25am Brilliant! (as usual)
It's much faster than MC, right?
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