Published July 21, 2021
| Version v1
Conference paper
Parallel Transport on Kendall Shape Spaces
Contributors
Others:
- Université Côte d'Azur (UCA)
- E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- CB - Centre Borelli - UMR 9010 (CB) ; Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université Paris Cité (UPCité)
- The authors have received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement G-Statistics N° 786854). It was also supported by the French government through the 3IA Côte d'Azur Investments ANR-19-P3IA-0002 managed by the National Research Agency.
- ANR-19-P3IA-0002,3IA@cote d'azur,3IA Côte d'Azur(2019)
- European Project: 786854,H2020 Pilier ERC,ERC AdG(2018)
Description
Kendall shape spaces are a widely used framework for the statistical analysis of shape data arising from many domains, often requiring the parallel transport as a tool to normalise time series data or transport gradient in optimisation procedures. We present an implementation of the pole ladder, an algorithm to compute parallel transport based on geodesic parallelograms and compare it to methods by integration of the parallel transport ordinary differential equation.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.inria.fr/hal-03160677
- URN
- urn:oai:HAL:hal-03160677v1
Origin repository
- Origin repository
- UNICA