A theory of self-calibration of a moving camera
International Journal of Computer Vision
Self-Calibration of Stationary Cameras
International Journal of Computer Vision
Kruppa's Equations Derived from the Fundamental Matrix
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices
International Journal of Computer Vision
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Stratified Self-Calibration with the Modulus Constraint
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Differential Algorithm for Motion Recovery: AGeometric Approach
International Journal of Computer Vision
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
The Role of Total Least Squares in Motion Analysis
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Autocalibration and the absolute quadric
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Critical Motion Sequences for Monocular Self-Calibration and Uncalibrated Euclidean Reconstruction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
Analytic Reduction of the Kruppa Equations
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Self-Calibration of a Simplified Camera Using Kruppa Equations
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Building detection and 3D reconstruction from two-view of monocular camera
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Building face reconstruction from sparse view of monocular camera
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
| Hi-index | 0.01 |
In this paper, we study general questions about the solvability of the Kruppa equations and show that, in several special cases, the Kruppa equations can be renormalized and become linear. In particular, for cases when the camera motion is such that its rotation axis is parallel or perpendicular to translation, we can obtain linear algorithms for self-calibration. A further study of these cases not only reveals generic difficulties with degeneracy in conventional self-calibration methods based on the nonlinear Kruppa equations, but also clarifies some incomplete discussion in the literature about the solutions of the Kruppa equations. We demonstrate that Kruppa equations do not provide sufficient constraints on camera calibration and give a complete account of exactly what is missing in Kruppa equations. In particular, a clear relationship between the Kruppa equations and chirality is revealed. The results then resolve the discrepancy between the Kruppa equations and the necessary and sufficient condition for a unique calibration. Simulation results are presented for evaluation of the sensitivity and robustness of the proposed linear algorithms.