Sobolev metrics on shape space of surfaces
Philipp Harms

TL;DR
This paper develops Sobolev inner metrics on shape space of surfaces, ensuring meaningful distances and geodesic equations, with applications demonstrated through numerical solutions.
Contribution
It introduces a general framework for Sobolev inner metrics on shape space, proving non-vanishing distances and well-posed geodesic equations without restrictions on dimensions.
Findings
Sobolev inner metrics induce non-vanishing path-length distances.
Geodesic equations are derived and shown to be well-posed.
Numerical solutions to geodesic equations are successfully computed.
Abstract
Many procedures in science, engineering and medicine produce data in the form of geometric shapes. Mathematically, a shape can be modeled as an un-parameterized immersed sub-manifold, which is the notion of shape used here. Endowing shape space with a Riemannian metric opens up the world of Riemannian differential geometry with geodesics, gradient flows and curvature. Unfortunately, the simplest such metric induces vanishing path-length distance on shape space. This discovery by Michor and Mumford was the starting point to a quest for stronger, meaningful metrics that should be able to distinguish salient features of the shapes. Sobolev metrics are a very promising approach to that. They come in two flavors: Outer metrics which are induced from metrics on the diffeomorphism group of ambient space, and inner metrics which are defined intrinsically to the shape. In this work, Sobolev…
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Taxonomy
TopicsMorphological variations and asymmetry
