• DocumentCode
    926137
  • Title

    Algorithms for matching 3D line sets

  • Author

    Kamgar-Parsi, B. ; Kamgar-Parsi, B.

  • Author_Institution
    Office of Naval Res., Arlington, VA, USA
  • Volume
    26
  • Issue
    5
  • fYear
    2004
  • fDate
    5/1/2004 12:00:00 AM
  • Firstpage
    582
  • Lastpage
    593
  • Abstract
    Matching two sets of lines is a basic tool that has applications in many computer vision problems such as scene registration, object recognition, motion estimation, and others. Line sets may be composed of infinitely long lines or finite length line segments. Depending on line lengths, three basic cases arise in matching sets of lines: 1) finite-finite, 2) finite-infinite, and 3) infinite-infinite. Case 2 has not been treated in the literature. For Cases 1 and 3, existing algorithms for matching 3D line sets are not completely satisfactory in that they either solve special situations, or give approximate solutions, or may not converge, or are not invariant with respect to coordinate system transforms. In this paper, we present new algorithms that solve exactly all three cases for the general situation. The algorithms are provably convergent and invariant to coordinate transforms. Experiments with synthetic and real 3D image data are reported.
  • Keywords
    computer vision; image matching; 3D image data; 3D line sets; computer vision; image matching algorithm; line matching; line segments; motion estimation; object recognition; scene registration; three dimensional image data; three dimensional line sets; Application software; Computer vision; Image converters; Image edge detection; Image reconstruction; Image segmentation; Laser radar; Layout; Motion estimation; Object recognition; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2004.1273930
  • Filename
    1273930