Géométrie différentielle

Parallel Transport on Kendall Shape Spaces

Publié le - GSI 2021 - 5th conference on Geometric Science of Information

Auteurs : Nicolas Guigui, Elodie Maignant, Alain Trouvé, Xavier Pennec

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.