@conference {14176,
title = {Motion constraint patterns},
booktitle = {, Proceedings of IEEE Workshop on Qualitative Vision, 1993},
year = {1993},
month = {1993/06/14/},
pages = {128 - 139},
publisher = {IEEE},
organization = {IEEE},
abstract = {The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, derivatives of the image flow) to 3-D motion and structure. Since it has proved very difficult to achieve accurate input (local image motion), a lot of effort has been devoted to the development of robust techniques. A new approach to the problem of egomotion estimation is taken, based on constraints of a global nature. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the three dimensional motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3-D 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. As a matter of fact, since only the sign of the normal flow measurement is employed, 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, computational geometry, Computer vision, correspondence, Educational institutions, egomotion recovery, Fluid flow measurement, geometric constraint, Geometrical optics, Image motion analysis, image plane, Laboratories, local image motion, local normal flow measurements, Motion estimation, Motion measurement, motion parameters, optical flow, Rotation measurement},
isbn = {0-8186-3692-0},
doi = {10.1109/WQV.1993.262942},
author = {Ferm{\"u}ller, Cornelia}
}