English

Deformable Voxel Grids for Shape Comparisons

Computer Vision and Pattern Recognition 2022-11-22 v1 Image and Video Processing Analysis of PDEs

Abstract

We present Deformable Voxel Grids (DVGs) for 3D shapes comparison and processing. It consists of a voxel grid which is deformed to approximate the silhouette of a shape, via energy-minimization. By interpreting the DVG as a local coordinates system, it provides a better embedding space than a regular voxel grid, since it is adapted to the geometry of the shape. It also allows to deform the shape by moving the control points of the DVG, in a similar manner to the Free Form Deformation, but with easier interpretability of the control points positions. After proposing a computation scheme of the energies compatible with meshes and pointclouds, we demonstrate the use of DVGs in a variety of applications: correspondences via cubification, style transfer, shape retrieval and PCA deformations. The first two require no learning and can be readily run on any shapes in a matter of minutes on modest hardware. As for the last two, they require to first optimize DVGs on a collection of shapes, which amounts to a pre-processing step. Then, determining PCA coordinates is straightforward and brings a few parameters to deform a shape.

Keywords

Cite

@article{arxiv.2211.11609,
  title  = {Deformable Voxel Grids for Shape Comparisons},
  author = {Raphaël Groscot and Laurent D. Cohen},
  journal= {arXiv preprint arXiv:2211.11609},
  year   = {2022}
}
R2 v1 2026-06-28T06:23:23.766Z