Recent advances in scanning technology and scientific
simulations can generate sample points from a geometric domain
at ease. Inferring the shape and their features from such
a simple light-weight input can be a very effective modeling paradigm
across many areas of science and engineering. In this talk
we will go over the techniques developed for such modeling
paradigms. In particular, we cover algorithms for
(i) extracting a surface out of point samples, (ii) computing
an approximate medial axis of the sampled object, (iii) segmenting
the object into so called ``features". Theoretical concepts along with
experimental results will be presented.
- Curve Reconstruction
- Surface Samples
- Surface Reconstruction
- Noisy samples
- Noise smoothing
- MLS techniques
- Sample Decimation
- Quality Meshing
- Large Data
- Octree subdivision
- Medial Axis Approximation
- Voronoi facet filtering
- Convergence guarantees
- Experimental results
- Shape Segmentation
- Flow and critical points
- Stable manifolds
Medial axis approximation
Shape segmentation and matching
Tutorial for the Fall School at Berlin, October, 2003
DL 266 TR 12:30-1:48
Office Hours : TR 2:00-2:30 or by appointment
Grading will be based on three things.
A. Experiment with the Cocone software (will be provided) on data from your application
and study its results.
B. A Term paper at the end of the course on a related topic of your choice.
C. Your class participation.