Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Paracatadioptric Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine Reconstruction from Perspective Image Pairs Obtained by a Translating Camera
Proceedings of the Second Joint European - US Workshop on Applications of Invariance in Computer Vision
Paracatadioptric Camera Calibration Using Lines
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Multi-View Geometry of 1D Radial Cameras and its Application to Omnidirectional Camera Calibration
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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 Factorization Based Self-Calibration for Radially Symmetric Cameras
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Self-calibration of a general radially symmetric distortion model
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Camera Models and Fundamental Concepts Used in Geometric Computer Vision
Foundations and Trends® in Computer Graphics and Vision
Generic Self-calibration of Central Cameras from Two Rotational Flows
International Journal of Computer Vision
Robust radial distortion from a single image
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Calibration of omnidirectional cameras in practice: A comparison of methods
Computer Vision and Image Understanding
International Journal of Computer Vision
Automatic Radial Distortion Estimation from a Single Image
Journal of Mathematical Imaging and Vision
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
Pattern Recognition Letters
| Hi-index | 0.00 |
We consider the self-calibration problem for a generic imaging model that assigns projection rays to pixels without a parametric mapping. We consider the central variant of this model, which encompasses all camera models with a single effective viewpoint. Self-calibration refers to calibrating a camera's projection rays, purely from matches between images, i.e. without knowledge about the scene such as using a calibration grid. In order to do this we consider specific camera motions, concretely, pure translations and rotations, although without the knowledge of rotation and translation parameters (rotation angles, axis of rotation, translation vector). Knowledge of the type of motion, together with image matches, gives geometric constraints on the projection rays. We show for example that with translational motions alone, self-calibration can already be performed, but only up to an affine transformation of the set of projection rays. We then propose algorithms for full metric self-calibration, that use rotational and translational motions or just rotational motions.