CS 284: CAGD
Lecture #22 -- Tue 11/06, 2012.
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Preparation: Study: Adaptively
Sampled Distance Fields
Warm-Up: Someone might direct the
following criticism at today's paper:
"The B-Rep of a 3D solid object is a 2D entity.
Does it make sense to represent a 2D manifold with sample
points in 3D?
Doesn't that unnecessarily increase complexity and data
volume?
(since volume complexity grwows with 3rd power, rather than
the 2nd power)"
1.) How would you respond to this
critique?
(Write down some key talking
points.)
2.) How does one reconstruct a
surface (in .STL format) from an ADF ?
Brandon leads
the discussion on:
Adaptively
Sampled Distance Fields
1.) In the
top-down approach for creating subdivided ADF cells, what are
the exact tests performed ?
2.) How is the gradient of the distance field computed ?
3.) In comparing the number of elements in Figures 4b and 4d,
are the authors doing a fair comparison ?
How might they be making the ADF
approach look particularly good in this example ?
4.) Name a couple of application domains that profit from the
ADF approach of shape representation.
5.) How does one reconstruct the surface from an ADF ?
Assignments for Thu. Nov. 8, 2012:
Study: IS'07:
Isosurface Stuffing: Fast Tetrahedral Meshes with Good Dihedral
Angles
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