Can multiple views make up for lack of camera registration?
Image and Vision Computing
Some Properties of the E Matrix in Two-View Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A theory of self-calibration of a moving camera
International Journal of Computer Vision
Canonical representations for the geometries of multiple projective views
Computer Vision and Image Understanding
Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices
International Journal of Computer Vision
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Self-Calibration of a Simplified Camera Using Kruppa Equations
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Combining mendonça-cipolla self-calibration and scene constraints
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
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A new autocalibration algorithm has been recently presented by Mendonça and Cipolla which is both simple and nearly globally convergent. Analysis of convergence is missing in the original article. This paper fills the gap, presenting an extensive experimental evaluation of the Mendonça and Cipolla algorithm, aimed at assessing both accuracy and sensitivity to initialization. Results show that its accuracy is fair, and - remarkably - it converges from almost everywhere. This is very significant, because most of the existing algorithms are either complicated or they need to be started very close to the solution.