Shape Aware Matching of Implicit Surfaces based on Thin Shell Energies

TL;DR

This paper presents a novel variational method for matching implicit surfaces modeled as thin elastic shells, incorporating membrane and bending energies, with proven well-posedness and demonstrated effectiveness on synthetic and real data.

Contribution

It introduces a shape-aware matching approach using a new elastic shell energy model with a rigorous mathematical foundation and efficient numerical implementation.

Findings

Method is mathematically well-posed with an existence proof.

Efficient finite element implementation with multilevel optimization.

Effective on synthetic and geometry processing examples.

Abstract

A shape sensitive, variational approach for the matching of surfaces considered as thin elastic shells is investigated. The elasticity functional to be minimized takes into account two different types of nonlinear energies: a membrane energy measuring the rate of tangential distortion when deforming the reference shell into the template shell, and a bending energy measuring the bending under the deformation in terms of the change of the shape operators from the undeformed into the deformed configuration. The variational method applies to surfaces described as level sets. It is mathematically well-posed and an existence proof of an optimal matching deformation is given. The variational model is implemented using a finite element discretization combined with a narrow band approach on an efficient hierarchical grid structure. For the optimization a regularized nonlinear conjugate gradient scheme and a cascadic multilevel strategy are used. The features of the proposed approach are studied for synthetic test cases and a collection of geometry processing examples.