• DocumentCode
    2240583
  • Title

    Fast alignment using probabilistic indexing

  • Author

    Olson, Clark F.

  • Author_Institution
    Comput. Sci. Div., Univ. of California, Berkeley, CA, USA
  • fYear
    1993
  • fDate
    15-17 Jun 1993
  • Firstpage
    387
  • Lastpage
    392
  • Abstract
    The alignment method is a model-based object recognition technique that determines possible object transformations from three hypothesized matches of model and image points. For images and/or models with many features, the running time of the alignment method can be large. Methods of reducing the number of matches that must be examined are presented. The techniques described are the use of the probabilistic indexing system, and the elimination of groups of model points that produce large errors in the transformation determined by the alignment method. Results are presented which show that it is possible to achieve a speedup of over two orders of magnitude while still finding a correct alignment
  • Keywords
    image recognition; image sequences; probability; alignment method; hypothesized matches; model-based object recognition; object transformations; probabilistic indexing; running time; Computer science; Image databases; Image recognition; Indexing; Object detection; Object recognition; Probability density function; Reflection; Testing; Tires; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
  • Conference_Location
    New York, NY
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-3880-X
  • Type

    conf

  • DOI
    10.1109/CVPR.1993.341101
  • Filename
    341101