LEAR’s main focus on vision

  1. Image features and descriptors,robust correspondence
  • lighting and viewpoint invariant image descriptors
    • affine-invariant interest points
    • histogram of oriented gradient appearance descriptors
    • 2D shape descriptors/3D object category representations
    • more powerful measures for visual salience, similarity, correspondence and spatial relations
  1. Visual recognition: Statistical modeling, machine learning
  • selection, evaluation and adaptation of existing methods and the development of new ones
    • deal with the huge volumes of data
    • handle “noisy” training data
    • capture enough domain information to allow generalization from just a few images rather than
      having to build large, carefully marked-up training databases

      Visual recognition requires the construction of exploitable visual models of particular objects and of object and scene categories.


      via http://lear.inrialpes.fr/lear2008.pdf


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