3D interpretation of conics and orthogonality
CVGIP: Image Understanding
Interpretation of conic motion and its applications
International Journal of Computer Vision
Conic Reconstruction and Correspondence From Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
A buyer's guide to conic fitting
BMVC '95 Proceedings of the 6th British conference on Machine vision (Vol. 2)
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Ellipsoid Reconstruction from Three Perspective Views
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
3D Pose Estimation from an n-Degree Planar Curved Feature in Two Perspective Views
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Multiple View Geometry of General Algebraic Curves
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision
Real-time line detection through an improved Hough transform voting scheme
Pattern Recognition
Conic Geometry and Autocalibration from Two Images
Journal of Mathematical Imaging and Vision
Direct type-specific conic fitting and eigenvalue bias correction
Image and Vision Computing
Global hand pose estimation by multiple camera ellipse tracking
Machine Vision and Applications
Geometry of single axis motions using conic fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We propose here a new method to recover the orientation and position of a plane by matching at least three projections of a conic lying on the plane itself. The procedure is based on rearranging the conic projection equations such that the non linear terms are eliminated. It works with any kind of conic and does not require that the shape of the conic is known a-priori. The method was extensively tested using ellipses, but it can also be used for hyperbolas and parabolas. It was further applied to pairs of lines, which can be viewed as a degenerate case of hyperbola, without requiring the correspondence problem to be solved first. Critical configurations and numerical stability have been analyzed through simulations. The accuracy of the proposed algorithm was compared to that of traditional algorithms and of a trinocular vision system using a set of landmarks.