Name
Abstract | ||
|---|---|---|
We propose a method to simultaneously compute scalar basis functions with an associated functional map for a given pair of triangle meshes. Unlike previous techniques that put emphasis on smoothness with respect to the Laplace-Beltrami operator and thus favor low-frequency eigenfunctions, we aim for a basis that allows for better feature matching. This change of perspective introduces many degrees of freedom into the problem allowing to better exploit non-smooth descriptors. To effectively search in this high-dimensional space of solutions, we incorporate into our minimization state-of-the-art regularizers. We solve the resulting highly non-linear and non-convex problem using an iterative scheme via the Alternating Direction Method of Multipliers. At each step, our optimization involves simple to solve linear or Sylvester-type equations. In practice, our method performs well in terms of convergence, and we additionally show that it is similar to a provably convergent problem. We show the advantages of our approach by extensively testing it on multiple datasets in a few applications including shape matching, consistent quadrangulation and scalar function transfer. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1111/cgf.14360 | COMPUTER GRAPHICS FORUM |
Keywords | DocType | Volume |
CCS Concepts, Computing methodologies -> Shape analysis | Journal | 40 |
Issue | ISSN | Citations |
5 | 0167-7055 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omri Azencot | 1 | 0 | 0.34 |
| Rongjie Lai | 2 | 239 | 19.84 |