• DocumentCode
    457161
  • Title

    Adaptive Step Size Window Matching for Detection

  • Author

    Mekuz, Nathan ; Derpanis, Konstantinos G. ; Tsotsos, John K.

  • Author_Institution
    Dept. of Comput. Sci. & Center for Vision Res., York Univ., Toronto, Ont.
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    259
  • Lastpage
    262
  • Abstract
    An often overlooked problem in matching lies in selecting an appropriate step size. The selection of the step size for real-time applications is critical both from the point of view of computational efficiency and detection performance. Current systems set the step size in an ad hoc manner. This paper describes an algorithm for selecting the step size based on a theoretical worst case analysis. We have implemented this adaptive step size method in an object detection algorithm. Experimental evaluation demonstrates the effectiveness of our proposed algorithm
  • Keywords
    image matching; object detection; adaptive step size window matching; object detection; step size selection; theoretical worst case analysis; Algorithm design and analysis; Application software; Computational efficiency; Computer science; Computer vision; Image reconstruction; Object detection; Optical devices; Stereo image processing; Stereo vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.224
  • Filename
    1699196