Combining persistent homology and invariance groups for shape comparison

12/27/2013
by   Patrizio Frosini, et al.
0

In many applications concerning the comparison of data expressed by R^m-valued functions defined on a topological space X, the invariance with respect to a given group G of self-homeomorphisms of X is required. While persistent homology is quite efficient in the topological and qualitative comparison of this kind of data when the invariance group G is the group Homeo(X) of all self-homeomorphisms of X, this theory is not tailored to manage the case in which G is a proper subgroup of Homeo(X), and its invariance appears too general for several tasks. This paper proposes a way to adapt persistent homology in order to get invariance just with respect to a given group of self-homeomorphisms of X. The main idea consists in a dual approach, based on considering the set of all G-invariant non-expanding operators defined on the space of the admissible filtering functions on X. Some theoretical results concerning this approach are proven and two experiments are presented. An experiment illustrates the application of the proposed technique to compare 1D-signals, when the invariance is expressed by the group of affinities, the group of orientation-preserving affinities, the group of isometries, the group of translations and the identity group. Another experiment shows how our technique can be used for image comparison.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/04/2012

G-invariant Persistent Homology

Classical persistent homology is a powerful mathematical tool for shape ...
research
03/07/2016

Position paper: Towards an observer-oriented theory of shape comparison

In this position paper we suggest a possible metric approach to shape co...
research
02/22/2020

On the law of the iterated logarithm and strong invariance principles in computational geometry

We study the law of the iterated logarithm (Khinchin (1933), Kolmogorov ...
research
02/22/2020

On the law of the iterated logarithm and strong invariance principles in stochastic geometry

We study the law of the iterated logarithm (Khinchin (1933), Kolmogorov ...
research
12/31/2018

Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning

The aim of this paper is to provide a general mathematical framework for...
research
06/04/2021

Provably Strict Generalisation Benefit for Invariance in Kernel Methods

It is a commonly held belief that enforcing invariance improves generali...
research
03/06/2018

Conceptualization of Object Compositions Using Persistent Homology

A topological shape analysis is proposed and utilized to learn concepts ...

Please sign up or login with your details

Forgot password? Click here to reset