Fast and Accurate Algorithms for Projective Multi-Image Structure from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Globally Convergent Autocalibration Using Interval Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variational Approach to Problems in Calibration of Multiple Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative Extensions of the Sturm/Triggs Algorithm: Convergence and Nonconvergence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stereo Self-adjustment Methodology for Resuming Active Camera Operation
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Scene point constraints in camera auto-calibration: an implementational perspective
Image and Vision Computing
Journal of Signal Processing Systems
Euclidean structure recovery from motion in perspective image sequences via Hankel rank minimization
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Maximum likelihood autocalibration
Image and Vision Computing
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This paper describes new techniques for self calibration and for recovering the motion from a projective reconstruction when the calibration is known. We show that our approach deals with the ambiguities in self calibration produced by special motions. We extend our techniques to deal with varying calibration parameters. In passing, we prove convergence for the iterative projective reconstruction algorithm of Sturm/Triggs and Berthilsson/Heyden/Sparr.