A parametric analysis of discrete Hamiltonian functional maps

Abstract

Abstract In this paper we develop an in-depth theoretical investigation of the discrete Hamiltonian eigenbasis, which remains quite unexplored in the geometry processing community. This choice is supported by the fact that Dirichlet eigenfunctions can be equivalently computed by defining a Hamiltonian operator, whose potential energy and localization region can be controlled with ease. We vary with continuity the potential energy and study the relationship between the Dirichlet Laplacian and the Hamiltonian eigenbases with the functional map formalism. We develop a global analysis to capture the asymptotic behavior of the eigenpairs. We then focus on their local interactions, namely the veering patterns that arise between proximal eigenvalues. Armed with this knowledge, we are able to track the eigenfunctions in all possible configurations, shedding light on the nature of the functional maps. We exploit the Hamiltonian-Dirichlet connection in a partial shape matching problem, obtaining state of the art results, and provide directions where our theoretical findings could be applied in future research.

Publication
Computer Graphics Forum
Emilian Postolache
Emilian Postolache
Senior AI Research Scientist

Senior AI Research Scientist @ Iris Audio

Marco Fumero
Marco Fumero
PhD Student
Luca Cosmo
Luca Cosmo
Assistant Professor
Emanuele Rodolà
Emanuele Rodolà
Full Professor