SFU Applied & Computational Math Seminar Series: Justin Solomon

In 3D modeling, medical imaging, and other disciplines, popular techniques for geometry processing often rely on mathematical models for surface geometry, viewing shapes as thin sheets embedded in $\mathbb{R}^3$; this construction neglects the fact that many of these surfaces are "boundary representations," intended to represent boundaries of volumes. As an alternative, in this talk we will explore how calculations on the extrinsic space around a surface can benefit geometry processing applications---as well as the mathematical, numerical, and computational challenges of this extension to three dimensions. Our algorithms for these problems will build on machinery from differential geometry, geometric measure theory, vector field design, and machine learning. 

(Joint work with several members of the MIT Geometric Data Processing Group.)