• DocumentCode
    3437214
  • Title

    A New Approach to Geometrical Feature Assessment for ICP-Based Pose Measurement: Continuum Shape Constraint Analysis

  • Author

    McTavish, D.J. ; Okouneva, G.

  • Author_Institution
    Ryerson Univ., Toronto
  • fYear
    2007
  • fDate
    5-7 Sept. 2007
  • Firstpage
    23
  • Lastpage
    32
  • Abstract
    This paper presents a generalization of closest- point constraint analysis called continuum shape constraint analysis (CSCA) that can be used to assess the suitability of whole objects or object features for range data scanning and subsequent pose estimation. "Directional CSCA" (D-CSCA) is proposed to specifically address pose estimation accuracy via the ICP (iterated closest-point) family of algorithms. Constraint analysis based on noise amplification index (NAI) is used. In the D-CSCA formulation, the continuum nature of the underlying shape registration renders the resulting gradient matrix and NAI thereof as pure properties of the feature, dependent on viewpoint but independent of the viewing instrument.
  • Keywords
    feature extraction; image registration; closest- point constraint analysis; continuum shape constraint analysis; geometrical feature assessment; noise amplification index; range data scanning; shape registration; subsequent pose estimation; Clouds; Computer errors; Cost function; Extraterrestrial measurements; Image analysis; Iterative closest point algorithm; Laser radar; Shape measurement; Space vehicles; Symmetric matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Image Processing Conference, 2007. IMVIP 2007. International
  • Conference_Location
    Kildare
  • Print_ISBN
    978-0-7695-2887-8
  • Type

    conf

  • DOI
    10.1109/IMVIP.2007.38
  • Filename
    4318134