Implicit Modular Deformations Analysis Library

IMODAL is a python librairy allowing to register shapes (curves, meshes, images) with structured large deformations. The structures are incorporated via deformation modules which generate vector fields of particular, chosen types. They can be defined explicitly (generating local scalings or rotations for instance) or implicitly from constraints. In addition, it is possible to combine them so that a complex structure can be easily defined as the superimposition of simple ones. Trajectories of such modular vector fields can then be integrated to build modular large deformations. Their parameters can be optimized to register observed shapes and analyzed.

Here is an example of reconstruction of basipetal growth using IMODAL:

_images/basipetal_learntmodel_reshoot_deformed_growth_0.png _images/basipetal_learntmodel_reshoot_deformed_growth_3.png _images/basipetal_learntmodel_reshoot_deformed_growth_5.png _images/basipetal_learntmodel_reshoot_deformed_growth_8.png _images/basipetal_learntmodel_reshoot_deformed_growth_10.png

IMODAL provides:

  • Registration of points clouds, curves, meshes and images

  • Atlas computation with hypertemplate

  • Estimation of the model parameters

  • tools to speed up and reduce the memory footprint ( such as GPU and KeOps support)


  • Benjamin Charlier

  • Barbara Gris

  • Leander Lacroix

  • Alain Trouvé

Related publications:

The project can be downloaded here.