CS: Two Meetings, Generalized sampling using a compound-eye imaging system, Compressive Geospatial Sensing, Polya Prize

Remi Gribonval sent me some information about some meetings of potential interest to readers of this blog:

The upcoming conference LVA on Latent Variable Analysis / Signal Separation, to be held in Saint-Malo, Britanny, France, will feature (among other):

• Two oral sessions on sparsity, sponsored by the FET-Open project SMALL
• http://lva2010.inria.fr/technical-program/oral-session-3-sparsity-i
• http://lva2010.inria.fr/technical-program/oral-session-4-sparsity-ii
• -plenaries by Stéphane Mallat and Pierre Comon       

More details can be found at http://lva2010.inria.fr/

A one day workshop on Sparsity and Learning (Apprentissage et Parcimonie), co-organized by Francis Bach and myself within the french network GDR ISIS, will feature invited lectures by: Stéphane Mallat, Guillaume Obozinski, Matthieu Kowalski, Jean-Christophe Pesquet, Erwan Lepennec, Cedric Fevotte, Alexandre Tsybakov, and Rémi Munos. More details to be found at at http://gdr-isis.org/rilk/gdr/ReunionListe-540

Thanks Remi.

I also just saw the following: Generalized sampling using a compound-eye imaging system for multi-dimensional object acquisition by Ryoichi Horisaki, Kerkil Choi, Joonku Hahn, Jun Tanida, and David J. Brady.  The abstract reads:

In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is sheared and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.

and a presentation entitled Towards Compressive Geospatial Sensing Via Fusion of LIDAR and Hyperspectral Imaging by Allen Y. Yang

The SIAM George Pólya Prize was awarded to Emmanuel Candès and Terence Tao. From the press release:

....The award recognizes their role in developing the theory of compressed sensing and matrix completion, which enables efficient reconstruction of sparse, high-dimensional data based on very few measurements. According to the selection committee, the algorithms and analysis are not only beautiful mathematics, worthy of study for their own sake, but they also lead to remarkable solutions of practical engineering problems...