@inproceedings{18392,
  abstract     = {Feature-based methods have recently gained popularity in computer vision and pattern recognition communities, in applications such as object recognition and image retrieval. In this paper, we explore analogous approaches in the 3D world applied to the problem of non-rigid shape search and retrieval in large databases.},
  author       = {Ovsjanikov, Maks and Bronstein, Alexander and Bronstein, Michael M. and Guibas, Leonidas J.},
  booktitle    = {12th International Conference on Computer Vision Workshops},
  isbn         = {9781424444427},
  location     = {Kyoto, Japan},
  publisher    = {IEEE},
  title        = {{Shape Google: A computer vision approach to isometry invariant shape retrieval}},
  doi          = {10.1109/iccvw.2009.5457682},
  year         = {2009},
}

@inproceedings{18393,
  abstract     = {Shape-from-X is a generic type of inverse problems in computer vision, in which a shape is reconstructed from some measurements. A specially challenging setting of this problem is the case in which the reconstructed shapes are non-rigid. In this paper, we propose a framework for intrinsic regularization of such problems. The assumption is that we have the geometric structure of a shape which is intrinsically (up to bending) similar to the one we would like to reconstruct. For that goal, we formulate a variation with respect to vertex coordinates of a triangulated mesh approximating the continuous shape. The numerical core of the proposed method is based on differentiating the fast marching update step for geodesic distance computation.},
  author       = {Devir, Yohai S. and Rosman, Guy and Bronstein, Alexander and Bronstein, Michael M. and Kimmel, Ron},
  booktitle    = {12th International Conference on Computer Vision Workshops},
  isbn         = {9781424444427},
  location     = {Kyoto, Japan},
  publisher    = {IEEE},
  title        = {{On reconstruction of non-rigid shapes with intrinsic regularization}},
  doi          = {10.1109/iccvw.2009.5457688},
  year         = {2009},
}