• DocumentCode
    2962612
  • Title

    A syntax for image understanding

  • Author

    Ahuja, Narendra

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2009
  • fDate
    20-25 June 2009
  • Firstpage
    9
  • Lastpage
    10
  • Abstract
    We consider one of the most basic questions in computer vision, that of finding a low-level image representation that could be used to seed diverse, subsequent computations of image understanding. Can we define a relatively general purpose image representation which would serve as the syntax for diverse needs of image understanding? What makes good image syntax? How do we evaluate it? We pose a series of such questions and evolve a set of answers to them, which in turn help evolve an image representation. For concreteness, we first perform this exercise in the specific context of the following problem.
  • Keywords
    computer vision; image representation; computer vision; image understanding syntax; low-level image representation; seed diverse image understanding; Computer vision; Humans; Image representation; Image segmentation; Layout; Object oriented modeling; Photometry; Probability distribution; Taxonomy; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops, 2009. CVPR Workshops 2009. IEEE Computer Society Conference on
  • Conference_Location
    Miami, FL
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4244-3994-2
  • Type

    conf

  • DOI
    10.1109/CVPRW.2009.5204337
  • Filename
    5204337