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1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97)
Uncalibrated 1D projective camera and 3D affine reconstruction of lines
Puerto Rico
June 17-June 19
ISBN: 0-8186-7822-4
ASCII Text
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Long Quan, "Uncalibrated 1D projective camera and 3D affine reconstruction of lines," Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, pp. 60, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997.
 
 
BibTex
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@article{ 10.1109/CVPR.1997.609298,
author = {Long Quan},
title = {Uncalibrated 1D projective camera and 3D affine reconstruction of lines},
journal ={Computer Vision and Pattern Recognition, IEEE Computer Society Conference on},
volume = {0},
year = {1997},
issn = {1063-6919},
pages = {60},
doi = {http://doi.ieeecomputersociety.org/10.1109/CVPR.1997.609298},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
TI - Uncalibrated 1D projective camera and 3D affine reconstruction of lines
SN - 1063-6919
SP
EP
A1 - Long Quan,
PY - 1997
KW - image reconstruction; 3D affine reconstruction; lines; shape; motion; line correspondences; 1D projective camera; uncalibrated affine cameras; 2D projective reconstruction; tensorial representation; image sequences; projection matrices; rescaling image coordinates
VL - 0
JA - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
ER -
 
Long Quan, CNRS, Montbonnot, France
We describe a linear algorithm to recover 3D affine shape/motion from line correspondences over three views with uncalibrated affine cameras. The key idea is the introduction of a one-dimensional projective camera. This converts the 3D affine reconstruction of "lines" into 2D projective reconstruction of "points". Using the full tensorial representation of three uncalibrated 1D views, we prove that the 3D affine reconstruction of lines from minimal data is unique up to a re-ordering of the views. 3D affine line reconstruction can be performed by properly rescaling image coordinates instead of using projection matrices. The algorithm is validated on both simulated and real image sequences.
Index Terms:
image reconstruction; 3D affine reconstruction; lines; shape; motion; line correspondences; 1D projective camera; uncalibrated affine cameras; 2D projective reconstruction; tensorial representation; image sequences; projection matrices; rescaling image coordinates
Citation:
Long Quan, "Uncalibrated 1D projective camera and 3D affine reconstruction of lines," cvpr, pp.60, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997
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