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This paper introduces a new mathematical and numerical framework for surface analysis derived from the general setting of elastic Riemannian metrics on shape spaces. Traditionally, those metrics are defined over the infinite dimensional…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Emmanuel Hartman , Emery Pierson , Martin Bauer , Mohamed Daoudi , Nicolas Charon

In the elastic shape analysis approach to shape matching and object classification, plane curves are represented as points in an infinite-dimensional Riemannian manifold, wherein shape dissimilarity is measured by geodesic distance. A…

Differential Geometry · Mathematics 2018-07-11 Tom Needham

This article is a survey of results involving conformal deformation of Riemannian metrics and fully nonlinear equations.

Differential Geometry · Mathematics 2007-05-23 Jeff Viaclovsky

This paper introduces a set of numerical methods for Riemannian shape analysis of 3D surfaces within the setting of invariant (elastic) second-order Sobolev metrics. More specifically, we address the computation of geodesics and geodesic…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Emmanuel Hartman , Yashil Sukurdeep , Eric Klassen , Nicolas Charon , Martin Bauer

Local and global illumination were recently defined in Riemannian manifolds to visualize classical Non-Euclidean spaces. This work focuses on Riemannian metric construction in $\mathbb{R}^3$ to explore special effects like warping, mirages,…

Graphics · Computer Science 2020-05-13 Tiago Novello , Vinícius da Silva , Luiz Velho

This paper studies a longitudinal shape transformation model in which shapes are deformed in response to an internal growth potential that evolves according to an advection reaction diffusion process. This model extends prior works that…

Analysis of PDEs · Mathematics 2021-01-19 Dai-Ni Hsieh , Sylvain Arguillère , Nicolas Charon , Laurent Younes

A Riemannian metric on a manifold M induces a family of Riemannian metrics on the loop space LM depending on a Sobolev space parameter s. We compute the connection forms of these metrics and the higher symbols of their curvature forms,…

Differential Geometry · Mathematics 2014-05-19 Yoshiaki Maeda , Steven Rosenberg , Fabián Torres-Ardila

This paper investigates spaces equipped with a family of metric-like functions satisfying certain axioms. These functions provide a unified framework for defining topology, uniformity, and diffeology. The framework is based on a family of…

General Topology · Mathematics 2026-03-25 Masaki Taho

We construct natural Riemannian metrics on Seiberg-Witten moduli spaces and study their geometry.

Differential Geometry · Mathematics 2009-11-13 Christian Becker

In this paper, we introduce restricted products for families of locally convex spaces and formulate criteria ensuring that mappings into such products are continuous or smooth. As a special case, can define restricted products of weighted…

Functional Analysis · Mathematics 2016-01-14 Boris Walter

We develop a geometric framework for generalized Milnor classifying spaces in the setting of diffeological spaces and infinite-dimensional geometry. Starting from Milnor's construction, we introduce spherical and projective models endowed…

Differential Geometry · Mathematics 2026-05-19 Jean-Pierre Magnot

Based on a local approximation of the Riemannian distance on a manifold by a computationally cheap dissimilarity measure, a time discrete geodesic calculus is developed, and applications to shape space are explored. The dissimilarity…

Numerical Analysis · Mathematics 2012-10-03 Martin Rumpf , Benedikt Wirth

It is well known that one can parameterize 2-D Riemannian structures by conformal transformations and diffeomorphisms of fiducial constant curvature geometries; and that this construction has a natural setting in general relativity theory…

General Relativity and Quantum Cosmology · Physics 2007-05-23 J. Gegenberg , G. Kunstatter

In shape analysis, the concept of shape spaces has always been vague, requiring a case-by-case approach for every new type of shape. In this paper, we give a general definition for an abstract space of shapes in a manifold. This notion…

Differential Geometry · Mathematics 2015-04-09 Sylvain Arguillère

For a given smooth manifold, we consider the moduli space of Riemannian metrics up to isometry and scaling. One can define a preorder on the moduli space by the size of isometry groups. We call a Riemannian metric that attains a maximal…

Differential Geometry · Mathematics 2022-10-05 Yuichiro Taketomi

While the problem of estimating a probability density function (pdf) from its observations is classical, the estimation under additional shape constraints is both important and challenging. We introduce an efficient, geometric approach for…

Methodology · Statistics 2018-04-05 Sutanoy Dasgupta , Debdeep Pati , Ian H. Jermyn , Anuj Srivastava

In this paper, I shall demonstrate that sufficiently high-dimensional closed positively-curved Riemannian manifolds are either diffeomorphic to a spherical space form, or isometric to a locally compact rank one symmetric space. This…

Metric Geometry · Mathematics 2016-08-05 Yashar Memarian

Metric spaces are a fundamental component of mathematics and have a paramount importance as a framework for measuring distance. They can be found in many different branches of mathematics, such as analysis and topology. This paper offers an…

General Topology · Mathematics 2025-10-30 Ismail Gemaledin , Iusuf Gemaledin

This paper describes a novel framework for computing geodesic paths in shape spaces of spherical surfaces under an elastic Riemannian metric. The novelty lies in defining this Riemannian metric directly on the quotient (shape) space, rather…

Differential Geometry · Mathematics 2016-11-17 Alice Barbara Tumpach , Hassen Drira , Mohamed Daoudi , Anuj Srivastava

What is the shortest path between two data points lying in a high-dimensional space? While the answer is trivial in Euclidean geometry, it becomes significantly more complex when the data lies on a curved manifold -- requiring a Riemannian…

Machine Learning · Computer Science 2025-11-04 Louis Béthune , David Vigouroux , Yilun Du , Rufin VanRullen , Thomas Serre , Victor Boutin