• DocumentCode
    1425882
  • Title

    Reducing “Structure from Motion”: a general framework for dynamic vision. 1. Modeling

  • Author

    Soatto, Stefano ; Perona, Pietro

  • Author_Institution
    Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA
  • Volume
    20
  • Issue
    9
  • fYear
    1998
  • fDate
    9/1/1998 12:00:00 AM
  • Firstpage
    933
  • Lastpage
    942
  • Abstract
    The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of apparently unrelated models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction. The “natural” dynamic model, derived from the rigidity constraint and the projection model, is first reduced by explicitly decoupling structure (depth) from motion. Then, implicit decoupling techniques are explored, which consist of imposing that some function of the unknown parameters is held constant. By appropriately choosing such a function, not only can we account for models seen so far in the literature, but we can also derive novel ones
  • Keywords
    image reconstruction; image sequences; motion estimation; recursive estimation; decoupling techniques; dynamic vision; dynamical system reduction; estimation techniques; modeling; monocular image sequences; projection model; recursive estimation; rigidity constraint; structure-from-motion recovery; Cameras; Geometry; Image analysis; Image reconstruction; Image sequences; Image storage; Layout; Motion estimation; Recursive estimation; Reduced order systems;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.713360
  • Filename
    713360