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Globally Convergent Autocalibration Using Interval Analysis
December 2004 (vol. 26 no. 12)
pp. 1633-1638
ASCII Text
x 
 
Andrea Fusiello, Arrigo Benedetti, Michela Farenzena, Alessandro Busti, "Globally Convergent Autocalibration Using Interval Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 12, pp. 1633-1638, December, 2004.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2004.125,
author = {Andrea Fusiello and Arrigo Benedetti and Michela Farenzena and Alessandro Busti},
title = {Globally Convergent Autocalibration Using Interval Analysis},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {26},
number = {12},
issn = {0162-8828},
year = {2004},
pages = {1633-1638},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2004.125},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Globally Convergent Autocalibration Using Interval Analysis
IS - 12
SN - 0162-8828
SP1633
EP1638
EPD - 1633-1638
A1 - Andrea Fusiello,
A1 - Arrigo Benedetti,
A1 - Michela Farenzena,
A1 - Alessandro Busti,
PY - 2004
KW - Image processing and computer vision
KW - camera calibration
KW - modeling from video
KW - interval arithmetic
KW - 3D/stereo scene analysis
KW - self-calibration.
VL - 26
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
We address the problem of autocalibration of a moving camera with unknown constant intrinsic parameters. Existing autocalibration techniques use numerical optimization algorithms whose convergence to the correct result cannot be guaranteed, in general. To address this problem, we have developed a method where an interval branch-and-bound method is employed for numerical minimization. Thanks to the properties of Interval Analysis this method converges to the global solution with mathematical certainty and arbitrary accuracy and the only input information it requires from the user are a set of point correspondences and a search interval. The cost function is based on the Huang-Faugeras constraint of the essential matrix. A recently proposed interval extension based on Bernstein polynomial forms has been investigated to speed up the search for the solution. Finally, experimental results are presented.

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Index Terms:
Image processing and computer vision, camera calibration, modeling from video, interval arithmetic, 3D/stereo scene analysis, self-calibration.
Citation:
Andrea Fusiello, Arrigo Benedetti, Michela Farenzena, Alessandro Busti, "Globally Convergent Autocalibration Using Interval Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 12, pp. 1633-1638, Dec. 2004, doi:10.1109/TPAMI.2004.125
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