• DocumentCode
    3192259
  • Title

    Minimum cost aspect classification: a module of a vision algorithm compiler

  • Author

    Hong, Ki Sang ; Ikeuchi, Katsushi ; Gremban, Keith D.

  • Author_Institution
    Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    i
  • fYear
    1990
  • fDate
    16-21 Jun 1990
  • Firstpage
    65
  • Abstract
    The authors present the design of a vision algorithm compiler module for object localization that is used to construct efficient vision programs for a subtask of object localization called aspect classification. Intuitively, an aspect is a representative appearance, and can be associated with a range of viewing positions. In object localization, an object is first classified into an aspect in order to obtain a rough estimate of an object´s configuration; this is followed by a numerical minimization procedure to locate the object precisely. The compiler module generates an optimal strategy for aspect classification, in the sense that the average cost of classification is minimal. The performance of the module is illustrated with several examples
  • Keywords
    computerised pattern recognition; computerised picture processing; minimisation; numerical methods; program compilers; aspect classification; configuration estimation; minimum cost aspect classification; numerical minimization; object localization; vision algorithm compiler; Aerospace electronics; Algorithm design and analysis; Computer science; Costs; Design optimization; Feature extraction; Machine vision; Optimizing compilers; Sensor systems; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1990. Proceedings., 10th International Conference on
  • Conference_Location
    Atlantic City, NJ
  • Print_ISBN
    0-8186-2062-5
  • Type

    conf

  • DOI
    10.1109/ICPR.1990.118066
  • Filename
    118066