From projective to Euclidean space under any practical situation, a criticism of self-calibration

被引:122
作者
Bougnoux, S [1 ]
机构
[1] INRIA, F-06902 Sophia Antipolis, France
来源
SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION | 1998年
关键词
Kruppa equations; projective versus Euclidean calibration; projective basis; focal length; 3D reconstruction;
D O I
10.1109/ICCV.1998.710808
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For many practical applications it is important to relax the self-calibration conditions to allow for changing internal camera parameters (e.g. zooming/focusing...). Classical techniques failed for such conditions. We present the available constraints that allow vs to right a projective calibration to a Euclidean one. Meanwhile, we found that the estimations of the internal parameters were rather inaccurate. We discuss theoretically this difficulty and above all the resulting effect on the 3D reconstruction. In fact, we show that the uncertainty on the focal length estimation leads to a Euclidean calibration vp to a quasi anisotropic homothety whereas the error on the principal point can often be interpreted as a translation. Hopefully, the calibration we come vp with, is quite acceptable for reconstruction of models.
引用
收藏
页码:790 / 796
页数:7
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