At present, a new algorithm of feature matching-SIFT has become a hot topic in the feature matching field, whose matching ability is strong, and could process the matching problems with translation, rotation and affine transformation among different images, and to a certain extent is with more stable feature matching ability for images which are captured from random different angles.In this paper, single camera is first calibrated using plane chessboard based on OpenCV,in order to overcome shortcomings in traditional and previous self-calibration methods, SIFT algorithm is proposed to calibrate stereo cameras after two cameras intrinsic parameters are calibrated. Fundamentalmatrix is gained through several matching points in two images using SIFT feature matching method, combined with intrinsic parameters, we can compute essential matrix. Translation matrix and the rotation matrix of stereo cameras can be resolved through SVD of essential matrix known as Huang- Faugeras constrains. Experiment results show that our method can calibrate relationship of stereo cameras accurately, and be able to calibrate two cameras in any circumstances. The algorithm has strong adaptability and robustness, but the expense time needs to be further improved.
[doi]
@inproceedings{Liu2009:Stereo,
author = {Ran Liu and Hua Zhang and Manlu Liu and Xianfeng Xia and Tianlian
Hu},
title = {Stereo Cameras Self-Calibration Based on SIFT},
booktitle = {Proceedings of the 2009 International Conference on Measuring Technology
and Mechatronics Automation (ICMTMA '09)},
year = {2009},
volume = {1},
pages = {352--355},
address = {Zhangjiajie, Hunan},
month = {April},
abstract = {At present, a new algorithm of feature matching-SIFT has become a
hot topic in the feature matching field, whose matching ability is
strong, and could process the matching problems with translation,
rotation and affine transformation among different images, and to
a certain extent is with more stable feature matching ability for
images which are captured from random different angles.In this paper,
single camera is first calibrated using plane chessboard based on
OpenCV,in order to overcome shortcomings in traditional and previous
self-calibration methods, SIFT algorithm is proposed to calibrate
stereo cameras after two cameras intrinsic parameters are calibrated.
Fundamentalmatrix is gained through several matching points in two
images using SIFT feature matching method, combined with intrinsic
parameters, we can compute essential matrix. Translation matrix and
the rotation matrix of stereo cameras can be resolved through SVD
of essential matrix known as Huang- Faugeras constrains. Experiment
results show that our method can calibrate relationship of stereo
cameras accurately, and be able to calibrate two cameras in any circumstances.
The algorithm has strong adaptability and robustness, but the expense
time needs to be further improved.},
acmid = {1606062},
days = {11-12},
doi = {http://dx.doi.org/10.1109/ICMTMA.2009.338},
isbn = {978-0-7695-3583-8},
keywords = {SIFT, Self-calibration, OpenCV, SVD, Huang- Faugeras' constrains},
numpages = {4},
}