@inproceedings{18396,
  abstract     = {We discuss the synthesis between the 3D and the 2D data in three-dimensional face recognition. We show how to compensate for the illumination and racial expressions using the 3D facial geometry and present the approach of canonical images, which allows us to incorporate geometric information into standard face recognition approaches.},
  author       = {Bronstein, Alexander and Bronstein, M.M. and Gordon, E. and Kimmel, R.},
  booktitle    = {2004 International Conference on Image Processing},
  isbn         = {0780385543},
  issn         = {1522-4880},
  location     = {Singapore, Singapore},
  publisher    = {IEEE},
  title        = {{Fusion of 2D and 3D data in three-dimensional face recognition}},
  doi          = {10.1109/icip.2004.1418696},
  year         = {2004},
}

@inproceedings{18397,
  abstract     = {We present a generic approach, which allows to adapt sparse blind deconvolution and blind source separation algorithms to arbitrary sources. The key idea is to bring the problem to the case in which the underlying sources are sparse by applying a sparsifying transformation on the mixtures. We present simulation results and show that such transformation can be found by training. Properties of the optimal sparsifying transformation are highlighted by an example with aerial images.},
  author       = {Bronstein, M.M. and Bronstein, Alexander and Zibulevsky, M. and Zeevi, Y.Y.},
  booktitle    = {2004 International Conference on Image Processing},
  isbn         = {0780385543},
  issn         = {1522-4880},
  location     = {Singapore, Singapore},
  publisher    = {IEEE},
  title        = {{Optimal sparse representations for blind source separation and blind deconvolution: A learning approach}},
  doi          = {10.1109/icip.2004.1421428},
  year         = {2001},
}