Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Camera calibration using spheres: A semi-definite programming approach
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Camera Calibration with One-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Geometric Interpretations of the Relation between the Image of the Absolute Conic and Sphere Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Calibration from Images of Spheres
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera calibration with moving one-dimensional objects
Pattern Recognition
Euclidean structure from N ≥ 2 parallel circles: theory and algorithms
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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A novel camera calibration algorithm for solving the problems of both circles based and spheres based camera calibration is proposed. By treating the images of both a circle and a sphere as a revolving stick, the introduced algorithm gives the constraint of the imaged absolute conic (IAC) with the help of the projected circle centers. It is also introduced on how to compute the projected circle centers of different calibration objects. Once the projected circle centers are computed, the Euclidean structure then can be determined by the constraint of the IAC. Experiments with simulated and real data are carried out to show the validity of the proposed camera calibration algorithm.