• DocumentCode
    1259649
  • Title

    Polynomial methods for structure from motion

  • Author

    Jerian, Charles ; Jain, Ramesh

  • Author_Institution
    Artificial Intelligence Lab., Michigan Univ., Ann Arbor, MI, USA
  • Volume
    12
  • Issue
    12
  • fYear
    1990
  • fDate
    12/1/1990 12:00:00 AM
  • Firstpage
    1150
  • Lastpage
    1166
  • Abstract
    The authors analyze the limitations of structure from motion (SFM) methods presented in the literature and propose the use of a polynomial system of equations, with the unit quaternions representing rotation, to recover SFM under perspective projection. The authors combine the equations by the method of resultants with the MAXIMA symbolic algebra system, reducing the system to a single polynomial. Its real roots are then found with Sturm sequences. Since this system has multiple solutions, a hypothesize-and-verify scheme is used to eliminate incorrect ones. The scheme diminishes the sensitivity of using polynomial equations. The authors examine the effect of different rotation axes and angles on SFM accuracy and compare the performance of the algorithm to a few earlier approaches. Generally, it is found that a large amount of motion is the most important factor in getting good SFM accuracy
  • Keywords
    pattern recognition; picture processing; polynomials; 2D image frames; 3D structure recovery; MAXIMA; Sturm sequences; pattern recognition; picture processing; polynomial; structure from motion; symbolic algebra system; Algebra; Artificial intelligence; Helium; Laboratories; Least squares methods; Nonlinear equations; Polynomials; Quaternions; Shape;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.62604
  • Filename
    62604