Performance of optical flow techniques
International Journal of Computer Vision
On the Convergence of the Lagged Diffusivity Fixed Point Method in Total Variation Image Restoration
SIAM Journal on Numerical Analysis
A Unifying Theory for Central Panoramic Systems and Practical Applications
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Non-Parametric Self-Calibration
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Are two rotational flows sufficient to calibrate a smooth non-parametric sensor?
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A unifying geometric representation for central projection systems
Computer Vision and Image Understanding - Special issue on omnidirectional vision and camera networks
Effective and Generic Structure from Motion using Angular Error
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Generic self-calibration of central cameras
Computer Vision and Image Understanding
Calibration of omnidirectional cameras in practice: A comparison of methods
Computer Vision and Image Understanding
On the global self-calibration of central cameras using two infinitesimal rotations
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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We address the self-calibration of a smooth generic central camera from only two dense rotational flows produced by rotations of the camera about two unknown linearly independent axes passing through the camera centre. We give a closed-form theoretical solution to this problem, and we prove that it can be solved exactly up to a linear orthogonal transformation ambiguity. Using the theoretical results, we propose an algorithm for the self-calibration of a generic central camera from two rotational flows.In order to solve the self-calibration problem using real images, we also study the computation of dense optical flows from image sequences acquired by the rotation of a smooth generic central camera. We propose a method for the computation of dense smooth generic flows from rotational camera motions using splines. The proposed methods are validated using both simulated and real image sequences.