Using vanishing points for camera calibration
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Euclidean structure from uncalibrated images
BMVC 94 Proceedings of the conference on British machine vision (vol. 2)
Stratified Self-Calibration with the Modulus Constraint
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Self-Calibration of Rotating and Zooming Cameras
International Journal of Computer Vision
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
From Reference Frames to Reference Planes: Multi-View Parallax Geometry and Applications
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Duality, Rigidity and Planar Parallax
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Camera Calibration with One-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Concentric Circles for Camera Calibration
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Euclidean Structure from Confocal Conics: Theory and Application to Camera Calibration
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Euclidean structure from N ≥ 2 parallel circles: theory and algorithms
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Semi-metric space: a new approach to treat orthogonality and parallelism
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Infinite homography estimation using two arbitrary planar rectangles
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Accurate camera calibration using the collinearity constraint
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
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Existing algorithms for camera calibration and metric reconstruction are not appropriate for image sets containing geometrically transformed images for which we cannot apply the camera constraints such as square or zero-skewed pixels. In this paper, we propose a framework to use scene constraints in the form of camera constraints. Our approach is based on image warping using images of parallelograms. We show that the warped image using parallelograms constrains the camera both intrinsically and extrinsically. Image warping converts the calibration problems of transformed images into the calibration problem with highly constrained cameras. In addition, it is possible to determine affine projection matrices from the images without explicit projective reconstruction. We introduce camera motion constraints of the warped image and a new parameterization of an infinite homography using the warping matrix. Combining the calibration and the affine reconstruction results in the fully metric reconstruction of scenes with geometrically transformed images. The feasibility of the proposed algorithm is tested with synthetic and real data. Finally, examples of metric reconstructions are shown from the geometrically transformed images obtained from the Internet.