Using vanishing points for camera calibration
International Journal of Computer Vision
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Self-Calibration from Image Triplets
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
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
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
PhotoBuilder -- 3D Models of Architectural Scenes from Uncalibrated Images
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Plane-based camera self-calibration by metric rectification of images
Image and Vision Computing
Full Camera Calibration from a Single View of Planar Scene
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A system for geometrically constrained single view reconstruction
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Self-calibration of a PTZ camera using new LMI constraints
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Structured light self-calibration with vanishing points
Machine Vision and Applications
Self-calibration of stationary non-rotating zooming cameras
Image and Vision Computing
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A common practice when carrying out self-calibration and Euclidean reconstruction from one or more views is to start with a guess at the principal point of the camera. The general belief is that inaccuracies in the estimation of the principal point do not have a significant effect on the other calibration parameters, or on reconstruction accuracy. It is the purpose of this paper to refute that belief. Indeed, it is demonstrated that the determination of the focal length of the camera is tied up very closely with the estimate of the principal point. Small changes in the estimated (sometimes merely guessed) principal point can cause very large changes in the estimated focal length, and the accuracy of reconstruction. In fact, the relative uncertainty in the focal length is inversely proportional to the distance of the principal point to the epipolar line. This analysis is geometric and exact, rather than experimental.