QC-OT: Optimal Transport with Quasiconformal Mapping

TL;DR

This paper introduces QC-OT, a topology-preserving optimal transport method for triangular meshes that employs quasiconformal mapping to maintain topological features during transport, enhancing applications in shape registration and image editing.

Contribution

The work develops a novel topology-preserving OT framework using quasiconformal correction, relaxing traditional triangulation constraints for better real-world deformation modeling.

Findings

Effective in shape registration and editing tasks

Maintains topological integrity during transport

Validated through multiple experiments

Abstract

The optimal transport (OT) map offers the most economical way to transfer one probability measure distribution to another. Classical OT theory does not involve a discussion of preserving topological connections and orientations in transmission results and processes. Existing numerical and geometric methods for computing OT seldom pays specific attention on this aspect. Especially, when dealing with the triangular mesh data, the known semi-discrete geometric OT (sd-OT) method employs critical operation of Delaunay triangulation (DT) to adapt topology to ensure the convexity of the energy function and the existence of the solution. This change in topology hampers the applicability of OT in modeling non-flip physical deformations in real-world tasks such as shape registration and editing problems in computer vision and medical imaging fields. This work introduces the topology structure-preserving optimal transport (QC-OT) map for the triangular mesh input. The computational strategy focuses on the two components: relaxing DT and convexity check in sd-OT and integrating quasiconformal (QC) correction. Here, quasiconformal mapping is employed to correct the regions unexpected distortions, and guarantee the topological preserving property of the transport. Furthermore, the spatial-temporal topology-preserving OT map is presented based t-OT to study the dynamics of the transportation. Multiple experiments have validated the efficiency and effectiveness of the proposed method and demonstrated its potential in the applications of mesh parameterization and image editing.