| Abstract |
Surface parameterization assigns coordinates to a surface by mapping it to a canonical domain, such as a disk or a sphere. These coordinates simplify geometry processing tasks, but their usefulness depends on how the map distorts angles, areas, and lengths. In this talk, I will present a variational framework for controlling distortion, focusing on numerical optimization for conformal, area-preserving, and distortion-balancing maps. Applications to surface registration and surface representation will be demonstrated to show how the choice of parameterization matters in practice. |
