maximize


@inproceedings{DrLiRuSc05,
  author = {Litke, Nathan and Droske, Mark and Rumpf, Martin and Schr{\"{o}}der,
	Peter},
  title = {An Image Processing Approach to Surface Matching},
  booktitle = {Proc. of Eurographics Symposium on Geometry Processing},
  year = {2005},
  pages = {207--216},
  abstract = {Establishing a correspondence between two surfaces is a basic ingredient
	in many geometry processing applications. Existing approaches, which
	attempt to match two embedded meshes directly, can be cumbersome
	to implement and it is often hard to produce accurate results in
	reasonable time. In this paper, we present a new variational method
	for matching surfaces that addresses these issues. Instead of matching
	two surfaces via a non-rigid deformation directly in $\mathbb{R}^3$,
	we apply well established matching methods from \emph{image processing}
	in the parameter domains of the surfaces. A matching energy is introduced
	which may depend on curvature, feature demarcations or surface textures,
	and a regularization energy controls length and area changes in the
	induced deformation between the two surfaces. The metric on both
	surfaces is properly incorporated into the formulation of the energy.
	This approach reduces all computations to the 2D setting while accounting
	for the original geometries. Consequently a fast multiresolution
	numerical algorithm for regular image grids can be applied to solve
	the global optimization problem. The final algorithm is robust, generically
	much simpler than direct matching methods, and computationally very
	fast for highly resolved triangle meshes.},
  owner = {bibtex}
}