@conference {14174,
	title = {Global 3D motion estimation},
	booktitle = {, 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1993. Proceedings CVPR {\textquoteright}93},
	year = {1993},
	month = {1993/06/15/17},
	pages = {415 - 421},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {It is shown how a monocular observer can estimate its 3D motion relative to the scene by using normal flow measurements in a global and qualitative way. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the 3D motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3D motion parameters can be found. The proposed algorithmic procedure is very robust, since it is not affected by small perturbations in the normal flow measurements. The direction of translation and the axis of rotation can be estimated with up to 100\% error in the image measurements},
	keywords = {3D motion parameters, Automation, axis of rotation, Computer vision, direction of translation, Educational institutions, Equations, Fluid flow measurement, global 3D motion estimation, Laboratories, Layout, monocular observer, Motion estimation, Motion measurement, normal flow measurements, Robustness, Rotation measurement, search problems, search technique, State estimation},
	isbn = {0-8186-3880-X},
	doi = {10.1109/CVPR.1993.341097},
	author = {Ferm{\"u}ller, Cornelia}
}
