In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine Structure from Line Correspondences With Uncalibrated Affine Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduced Multilinear Constraints: Theory and Experiments
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-Way Ambiguity in 2D Projective Reconstruction from Three Uncalibrated 1D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Marr Prize Special Issue
Computation of the Quadrifocal Tensor
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Common Framework for Multiple View Tensors
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
The Radial Trifocal Tensor: A Tool for Calibrating the Radial Distortion of Wide-Angle Cameras
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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
Conjugate gradient on Grassmann manifolds for robust subspace estimation
Image and Vision Computing
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In this paper a general procedure is given for reconstruction of a set of feature points in an arbitrary dimensional projective space from their projections into lower dimensional spaces. This extends the methods applied in the well-studied problem of reconstruction of scene points in 驴3 given their projections in a set of images. In this case, the bifocal, trifocal and quadrifocal tensors are used to carry out this computation. It is shown that similar methods will apply in a much more general context, and hence may be applied to projections from 驴 n to 驴 m , which have been used in the analysis of dynamic scenes, and in radial distortion correction. For sufficiently many generic projections, reconstruction of the scene is shown to be unique up to projectivity, except in the case of projections onto one-dimensional image spaces (lines), in which case there are two solutions.Projections from 驴 n to 驴2 have been considered by Wolf and Shashua (in International Journal of Computer Vision 48(1): 53---67, 2002), where they were applied to several different problems in dynamic scene analysis. They analyzed these projections using tensors, but no general way of defining such tensors, and computing the projections was given. This paper settles the general problem, showing that tensor definition and retrieval of the projections is always possible.