Implicit Minimal Surfaces for Bijective Correspondences
We introduce a new implicit representation of maps \(\varphi : A \to B\)
between triangle meshes \(A\) and \(B\), encoding the maps as the zero sets of complex
functions \(z\) on the product space \(A \times B\). In this representation we can
compute high-quality orientation-preserving bijections between \(A\) and \(B\) by
minimizing a simple Ginzburg-Landau energy, without requiring any combinatorial mesh
modifications, barrier functions, or a bijective initialization. Once an implicit map
has been computed, it encodes not only the vertex map, but also the entire overlay mesh
under the correspondence.
We introduce an implicit representation of continuous, bijective, orientation-preserving
maps between genus zero surfaces with or without boundary. The distortion of these maps can
easily be minimized by optimizing the Ginzburg-Landau functional---a ubiquitous model in
physics and differential geometry---leading to a simple algorithm for computing bijective
correspondences using only standard tools of the tangent vector field toolbox. The method
avoids combinatorial mesh modifications and does not require barrier functions to enforce
bijectivity making it more robust to noise and simpler to implement. Moreover, the algorithm
does not assume a bijective initialization and can untangle non-bijective correspondences
generated by computationally cheaper methods such as functional maps. It supports the use of
both landmark points and landmark curves to guide the correspondence. The key idea is that a
bijection between surfaces defines a two-dimensional mapping surface sitting inside the
four-dimensional product space of the two inputs, and this mapping surface can be stored
implicitly as the zero set of a complex section---essentially a complex function defined on
the product space. Now the distortion of the map can be optimized by minimizing the area of
this mapping surface, which amounts to minimizing the Ginzburg-Landau functional of the
complex section. We demonstrate the practical benefits of our method by comparing to
state-of-the-art correspondence algorithms and show that our implicit representation offers
improved stability and naturally supports constraints that are difficult to enforce with
explicit map representations.