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
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