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Sixth International Conference on Computer Vision (ICCV'98)
From Projective to Euclidean Space Under any Practical Situation, a Criticism of Self-Calibration
Bombay, India
January 04-January 07
ISBN: 81-7319-221-9
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 us 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 up to a quasi anisotropic homothety whereas the error on the principal point can often be interpreted as a translation. Hopefully, the calibration we come up with, is quite acceptable for reconstruction of models.
Index Terms:
Kruppa equations,Projective versus Euclidean calibration, Projective basis, Focal length, 3D Reconstruction
Citation:
Sylvain Bougnoux, "From Projective to Euclidean Space Under any Practical Situation, a Criticism of Self-Calibration," iccv, pp.790, Sixth International Conference on Computer Vision (ICCV'98), 1998
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