@inproceedings{18347,
  abstract     = {Multi-part shape matching is an important class of problems, arising in many fields such as computational archaeology, biology, geometry processing, computer graphics and vision. In this paper, we address the problem of simultaneous matching and segmentation of multiple shapes. We assume to be given a reference shape and multiple parts partially matching the reference. Each of these parts can have additional clutter, have overlap with other parts, or there might be missing parts. We show experimental results of efficient and accurate assembly of fractured synthetic and real objects.},
  author       = {Litany, Or and Bronstein, Alexander and Bronstein, Michael M.},
  booktitle    = {Computer Vision, ECCV 2012 - Workshops and Demonstrations},
  isbn         = {9783642338625},
  issn         = {1611-3349},
  location     = {Florence, Italy},
  number       = {Part 1},
  pages        = {1--11},
  publisher    = {Springer Nature},
  title        = {{Putting the pieces together: Regularized multi-part shape matching}},
  doi          = {10.1007/978-3-642-33863-2_1},
  volume       = {7583},
  year         = {2012},
}

@inproceedings{18348,
  abstract     = {We present a novel method for estimation of articulated motion in depth scans. The method is based on a framework for regularization of vector- and matrix- valued functions on parametric surfaces.

We extend augmented-Lagrangian total variation regularization to smooth rigid motion cues on the scanned 3D surface obtained from a range scanner. We demonstrate the resulting smoothed motion maps to be a powerful tool in articulated scene understanding, providing a basis for rigid parts segmentation, with little prior assumptions on the scene, despite the noisy depth measurements that often appear in commodity depth scanners.},
  author       = {Rosman, Guy and Bronstein, Alexander and Bronstein, Michael M. and Tai, Xue-Cheng and Kimmel, Ron},
  booktitle    = {Computer Vision, ECCV 2012 - Workshops and Demonstrations},
  isbn         = {9783642338625},
  issn         = {1611-3349},
  location     = {Florence, Italy},
  number       = {Part 1},
  pages        = {52--62},
  publisher    = {Springer Nature},
  title        = {{Group-valued regularization for analysis of articulated motion}},
  doi          = {10.1007/978-3-642-33863-2_6},
  volume       = {7583},
  year         = {2012},
}

@inproceedings{18349,
  abstract     = {The rapid development of 3D acquisition technology has brought with itself the need to perform standard signal processing operations such as filters on 3D data. It has been shown that the eigenfunctions of the Laplace-Beltrami operator (manifold harmonics) of a surface play the role of the Fourier basis in the Euclidean space; it is thus possible to formulate signal analysis and synthesis in the manifold harmonics basis. In particular, geometry filtering can be carried out in the manifold harmonics domain by decomposing the embedding coordinates of the shape in this basis. However, since the basis functions depend on the shape itself, such filtering is valid only for weak (near all-pass) filters, and produces severe artifacts otherwise. In this paper, we analyze this problem and propose the fractional filtering approach, wherein we apply iteratively weak fractional powers of the filter, followed by the update of the basis functions. Experimental results show that such a process produces more plausible and meaningful results.},
  author       = {Kovnatsky, Artiom and Bronstein, Michael M. and Bronstein, Alexander},
  booktitle    = {Computer Vision, ECCV 2012 - Workshops and Demonstrations},
  isbn         = {9783642338625},
  issn         = {0302-9743},
  location     = {Florence, Italy},
  number       = {Part 1},
  pages        = {83--91},
  publisher    = {Springer Nature},
  title        = {{Stable Spectral Mesh Filtering}},
  doi          = {10.1007/978-3-642-33863-2_9},
  volume       = {7583},
  year         = {2012},
}