@ARTICLE{koeser-08-conjugaterotation,
title={Conjugate rotation: Parameterization and estimation from an affine feature correspondence},
author={K{\"o}ser, Kevin and Beder, Christian and Koch, Reinhard},
journal={Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on},
year={2008},
month={June},
volume={},
number={},
pages={1-8},
abstract={When rotating a pinhole camera, images are related by the infinite homography KRK−1, which is algebraically a conjugate rotation. Although being a very common image transformation, e.g. important for self-calibration or panoramic image mosaicing, it is not completely understood yet. We show that a conjugate rotation has 7 degrees of freedom (as opposed to 8 for a general homography) and give a minimal parameterization. To estimate the conjugate rotation, authors traditionally made use of point correspondences, which can be seen as local zero order Taylor approximations to the image transformation. Recently however, affine feature correspondences have become increasingly popular. We observe that each such affine correspondence now provides a local first order Taylor approximation, which has not been exploited in the context of geometry estimation before. Using those two novel concepts above, we finally show that it is possible to estimate a conjugate rotation from a single affine feature correspondence under the assumption of square pixels and zero skew. As a byproduct, the proposed algorithm directly yields rotation, focal length and principal point.},
doi={10.1109/CVPR.2008.4587796},
ISSN={1063-6919}, }