Efficient deformable shape correspondence via kernel matching

Abstract

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior on the mapping, and propose a projected descent optimization procedure inspired by difference of convex functions (DC) programming.

Publication
Proc. Int’l Conference on 3D Vision (3DV)
Emanuele Rodolà
Emanuele Rodolà
Full Professor