A theory of self-calibration of a moving camera
International Journal of Computer Vision
Conic Reconstruction and Correspondence From Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
From Projective to Euclidean Space Under any Practical Situation, a Criticism of Self-Calibration
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
On the Absolute Quadratic Complex and Its Application to Autocalibration
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Focal length calibration from two views: method and analysis of singular cases
Computer Vision and Image Understanding
The Absolute Line Quadric and Camera Autocalibration
International Journal of Computer Vision
Linear pose estimate from corresponding conics
Pattern Recognition
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We show how the classical theory of projective conics provides new insights and results on the problem of 3D reconstruction from two images taken with uncalibrated cameras. The close relationship between Kruppa equations and Poncelet's Porism is investigated, leading, in particular, to a closed-form geometrically meaningful parameterization of the set of Euclidean reconstructions compatible with two images taken with cameras with constant intrinsic parameters and known pixel shape. An experiment with real images, showing the applicability of the method, is included.