• DocumentCode
    1742694
  • Title

    Recognizing articulated objects using invariance

  • Author

    Weiss, Isaac ; Ray, Manjit

  • Author_Institution
    Center for Autom. Res., Maryland Univ., College Park, MD, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    55
  • Abstract
    Articulated objects can have many degrees of freedom. Recognizing such an object in a single image can involve a search in a high-dimensional space that involves all these degrees of freedom, in addition to the usual unknown viewpoint. In this paper we use invariance to reduce this search space to a manageable size. Our method avoids feature detection for improved robustness. We apply the method to range images of objects such as back-hoes
  • Keywords
    feature extraction; image segmentation; invariance; object recognition; pattern matching; articulated object recognition; feature extraction; high-dimensional space; image segmentation; invariance; pattern matching; range images; search space; Arm; Automation; Educational institutions; Feature extraction; Image databases; Image recognition; Image segmentation; Noise robustness; Noise shaping; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.905275
  • Filename
    905275