In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theory and Practice of Projective Rectification
International Journal of Computer Vision
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
International Journal of Computer Vision
Optimal Motion and Structure Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Epipolar line estimation and rectification for stereo image pairs
IEEE Transactions on Image Processing
Which pattern? Biasing aspects of planar calibration patterns and detection methods
Pattern Recognition Letters
Video synchronization and its application to object transfer
Image and Vision Computing
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Computational stereo camera system with programmable control loop
ACM SIGGRAPH 2011 papers
Estimation of F-Matrix and image rectification by double quaternion
Information Sciences: an International Journal
Multispectral piecewise planar stereo using Manhattan-world assumption
Pattern Recognition Letters
Closed-form stereo image rectification
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Geometric and colorimetric error compensation for multi-view images
Journal of Visual Communication and Image Representation
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This paper describes a direct, self-contained method for planar image rectification of stereo pairs. The method is based solely on an examination of the Fundamental matrix, where an improved method is given for the derivation of two projective transformations that horizontally align all the epipolar projections. A novel approach is proposed to uniquely optimise each transform in order to minimise perspective distortions. This ensures the rectified images resemble the original images as closely as possible. Detailed results show that the rectification precision exactly matches the estimation error of the Fundamental matrix. In tests the remaining perspective distortion offers on average less than one percent viewpoint distortion. Both these factors offer superior robustness and performance compared with existing techniques.