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Automated Shape Recognition via Discrete Analytic Function Theory
Student-Run Geometry/Topology| Speaker: | Matt Stamps, UC Davis |
| Location: | 2112 MSB |
| Start time: | Tue, Nov 10 2009, 12:10PM |
Description
Automated processes for recognizing geometric features of objects in
3-space have numerous applications in computer graphics, physical
sciences, and biology. I will introduce a new approach for determining
shape features of closed surfaces in $\R^3$ using discrete analytic
function theory. This approach not only determines key feature points,
but gives a measure on how close two surfaces are from being isometric. I
will provide all necessary background information and give real life
applications to the protein classification problem.