Frank R. Schmidt

We propose a novel method for computing a geometrically consistent and spatially dense matching between two 3D shapes. Rather than mapping points to points we match infinitesimal surface patches while preserving the geometric structures. In this spirit we consider matchings as diffeomorphisms between the objects' surfaces which are by definition geometrically consistent. Based on the observation that such diffeomorphisms can be represented as closed and continuous surfaces in the product space of the two shapes we are led to a minimal surface problem in this product space. The proposed discrete formulation describes the search space with linear constraints. Computationally, our approach leads to a binary linear program whose relaxed version can be solved efficiently in a globally optimal manner. As cost function for matching, we consider a thin shell energy, measuring the physical energy necessary to deform one shape into the other. Experimental results demonstrate that the proposed LP relaxation allows to compute high-quality matchings which reliably put into correspondence articulated 3D shapes. Moreover a quantitative evaluation shows improvements over existing works.

@InProceedings\{WSSC11,
  author       = "Windheuser, Thomas and Schlickewei, Ulrich and Schmidt, Frank R. and Cremers, Daniel",
  title        = "Geometrically Consistent Elastic Matching of 3D Shapes: A Linear Programming Solution",
  booktitle    = "IEEE International Conference on Computer Vision (ICCV)",
  pages        = "2134--2141",
  month        = "Nov",
  year         = "2011",
  address      = "Barcelona, Spain",
  url          = "http://frank-r-schmidt.de/Publications/2011/WSSC11"
}