Alec's Web Log

I put up a project page for our new paper that we’ll present at SGP (Symposium of Geometry Processing) this month. The paper’s called, “Smooth Shape-Aware Functions with Controlled Extrema” and it’s a collaboration between me, my advisor, Olga Sorkine and my ex- officemate at NYU Tino Weinkauf, who’s now at MPI in Saarbrucken.

Abstract:
Functions that optimize Laplacian-based energies have become popular in geometry processing, e.g. for shape deformation, smoothing, multi scale kernel construction and interpolation. Minimizers of Dirichlet energies, or solutions of Laplace equations, are harmonic functions that enjoy the maximum principle, ensuring no spurious local extrema in the interior of the solved domain occur. However, these functions are only C⁰ at the constrained points, which often causes smoothness problems. For this reason, many applications optimize higher-order Laplacian energies such as biharmonic or triharmonic. Their minimizers exhibit increasing orders of continuity but also increasing oscillation, immediately releasing the maximum principle. In this work, we identify characteristic artifacts caused by spurious local extrema, and provide a framework for minimizing quadratic energies on manifolds while constraining the solution to obey the maximum principle in the solved region. Our framework allows the user to specify locations and values of desired local maxima and minima, while preventing any other local extrema. We demonstrate our method on the smoothness energies corresponding to popular polyharmonic functions and show its usefulness for fast handle-based shape deformation, controllable color diffusion, and topologically-constrained data smoothing.