generative modeling for Rhino
Force driven metaball meshing
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).
Comment
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Comment by Hrvoje Petrovic on October 10, 2011 at 1:25am -
Great!
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Comment by Daniel Piker on October 9, 2011 at 2:30am -
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
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Comment by Pieter Segeren on October 8, 2011 at 1:39pm -
Way cool! Even wíth the gaps for now.
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Comment by Daniel Kautz on October 8, 2011 at 12:48pm -
Great idea
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Comment by Astrid G on October 8, 2011 at 11:52am -
Amazing!
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Comment by Andy Payne on October 8, 2011 at 11:18am -
Very nice!
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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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Comment by Daniel Piker on October 8, 2011 at 9:21am
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