• DocumentCode
    1375989
  • Title

    Dominant-subspace invariants

  • Author

    Arnold, D.G. ; Sturtz, Kirk ; Velten, Vince ; Nandhakumar, N.

  • Author_Institution
    Wright-Patterson AFB, Air Force Res. Lab., Dayton, OH, USA
  • Volume
    22
  • Issue
    7
  • fYear
    2000
  • fDate
    7/1/2000 12:00:00 AM
  • Firstpage
    649
  • Lastpage
    662
  • Abstract
    Object recognition requires robust and stable features that are unique in feature space. Lie group analysis provides a constructive procedure to determine such features, called invariants, when they exist. Absolute invariants are rare in general, so quasi-invariants relax the restrictions required for absolute invariants and, potentially, can be just as useful in real-world applications. The paper develops the concept of a dominant-subspace invariant, a particular type of quasi-invariant, using the theory of Lie groups. A constructive algorithm is provided that fundamentally seeks to determine an integral submanifold which, in practice, is a good approximation to the orbit of the Lie group action. This idea is applied to the long-wave infrared problem and experimental results are obtained supporting the approach. Other application areas are cited
  • Keywords
    Lie groups; infrared imaging; invariance; object recognition; Lie group action; Lie group analysis; absolute invariants; constructive algorithm; dominant-subspace invariants; feature space; integral submanifold; long-wave infrared problem; quasi-invariants; Approximation algorithms; Force sensors; Intelligent sensors; Kirk field collapse effect; Lighting; Object recognition; Physics; Robustness; Sensor phenomena and characterization; Solid modeling;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.865182
  • Filename
    865182