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Computing Rectifying Homographies for Stereo Vision

Charles T. Loop, Zhengyou Zhang
CVPR 1999 pp. 1125-1131
doi:10.1109/CVPR.1999.786928 /cvpr/1999/loop1999cvpr-computing/

Abstract

Image rectification is the process of applying a pair of 2D projective transforms, or homographies, to a pair of images whose epipolar geometry is known so that epipolar lines in the original images map to horizontally aligned lines in the transformed images. We propose a novel technique for image rectification based on geometrically well defined criteria such that image distortion due to rectification is minimized. This is achieved by decomposing each homography into a specialized projective transform, a similarity transform, followed by a shearing transform. The effect of image distortion at each stage is carefully considered.

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Cite

Text

Loop and Zhang. "Computing Rectifying Homographies for Stereo Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999. doi:10.1109/CVPR.1999.786928

Markdown

[Loop and Zhang. "Computing Rectifying Homographies for Stereo Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999.](https://mlanthology.org/cvpr/1999/loop1999cvpr-computing/) doi:10.1109/CVPR.1999.786928

BibTeX

@inproceedings{loop1999cvpr-computing,
  title     = {{Computing Rectifying Homographies for Stereo Vision}},
  author    = {Loop, Charles T. and Zhang, Zhengyou},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1999},
  pages     = {1125-1131},
  doi       = {10.1109/CVPR.1999.786928},
  url       = {https://mlanthology.org/cvpr/1999/loop1999cvpr-computing/}
}