Numerical recipes: the art of scientific computing
Numerical recipes: the art of scientific computing
Using vanishing points for camera calibration
International Journal of Computer Vision
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using bilateral symmetry to improve 3D reconstruction from image sequences
Computer Vision and Image Understanding
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algebraic Geometry and Computer Vision: Polynomial Systems, Real andComplex Roots
Journal of Mathematical Imaging and Vision
Constrained Structure and Motion From Multiple Uncalibrated Views of a Piecewise Planar Scene
International Journal of Computer Vision
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Interactive Construction of 3D Models from Panoramic Mosaics
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Method for 3D Reconstruction of Piecewise Planar Objects from Single Panoramic Images
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Modeling and Rendering Architecture from Photographs:
Modeling and Rendering Architecture from Photographs:
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Shoes as a Platform for Vision
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
On Symmetry and Multiple-View Geometry: Structure, Pose, and Calibration from a Single Image
International Journal of Computer Vision
Single view metrology from scene constraints
Image and Vision Computing
Stabilizing 3D modeling with geometric constraints propagation
Computer Vision and Image Understanding
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We present a method to reconstruct from one or more images a scene that is rich in planes, alignments, symmetries, orthogonalities, and other forms of geometrical regularity. Given image points of interest and some geometric information, the method recovers least-squares estimates of the 3D points, camera position(s), orientation(s), and eventually calibration(s). Our contributions lie (i) in a novel way of exploiting some types of symmetry and of geometric regularity, (ii) in treating indifferently one or more images, (iii) in a geometric test that indicates whether the input data uniquely defines a reconstruction, and (iv) a parameterization method for collections of 3D points subject to geometric constraints. Moreover, the reconstruction algorithm lends itself to sensitivity analysis. The method is benchmarked on synthetic data and its effectiveness is shown on real-world data.