@string{springer="Springer"}
@Article{frohlich-etal2015,
  author =	 {Robert Frohlich and Levente Tamas and Zoltan Kato},
  title =	 {Homography Estimation between Omnidirectional Cameras without Point Correspondences},
  booktitle =	 {Handling Uncertainty and Networked Structure in Robot Control},
  publisher =	 springer,
  year =	 2015,
  editor =	 {Lucian Busoniu and Levente Tamas},
  chapter =	 6,
  pages =	 {129--151},
  abstract =	 {This chapter presents a novel approach for homography estimation between omnidirectional cameras. The solution is formulated in terms of a system of nonlinear equations. Each equation is generated by integrating a nonlinear function over corresponding image regions on the surface of the unit spheres representing the cameras. The method works without point correspondences or complex similarity metrics, using only a pair of corresponding planar regions extracted from the omnidirectional images. Relative pose of the cameras can be factorized from the estimated homography. The efficiency and robustness of the proposed method has been confirmed on both synthetic and real data.}
}