Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Projective Reconstruction and Invariants from Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparison of projective reconstruction methods for pairs of views
Computer Vision and Image Understanding
Robust detection of degenerate configurations while estimating the fundamental matrix
Computer Vision and Image Understanding
Stratified Self-Calibration with the Modulus Constraint
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theory and Practice of Projective Rectification
International Journal of Computer Vision
A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Digital Picture Processing
A new image rectification algorithm
Pattern Recognition Letters
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Cylindrical rectification to minimize epipolar distortion
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Stereo effect of image converted from planar
Information Sciences: an International Journal
Stereo rectification of uncalibrated and heterogeneous images
Pattern Recognition Letters
Estimation of F-Matrix and image rectification by double quaternion
Information Sciences: an International Journal
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An algorithm for the rectification of uncalibrated images is presented and applied to a variety of cases. The algorithm generates the rectifying transformations directly from the geometrical relationship between the images, using any three correspondences in the images to define a reference plane. A small set of correspondences is used to calculate an initial rectification. Additional correspondences are introduced semi-automatically, by correlating regions of the rectified images. Since the rectified images of surfaces in the reference plane have no relative distortion, features can be matched very accurately by correlation, allowing small changes in disparity to be detected. In the 3-d reconstruction of an architectural scene, differences in depth are resolved to about 0.001 of the distance from camera to subject.