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Qualitative egomotion
Authors:Cornelia Fermüller  Yiannis Aloimonos
Affiliation:(1) Department for Pattern Recognition and Image Processing, Institute for Automation, Technical University of Vienna, Treitlstraße 3, A-1040 Vienna, Austria;(2) Computer Vision Laboratory, Center for Automation Research, Computer Science Department and Institute for Advanced Computer Studies, University of Maryland, 20742-3411 College Park, MD
Abstract:Due to the aperture problem, the only motion measurement in images, whose computation does not require any assumptions about the scene in view, is normal flow—the projection of image motion on the gradient direction. In this paper we show how a monocular observer can estimate its 3D motion relative to the scene by using normal flow measurements in a global and qualitative way. The problem is addressed through a search technique. By checking constraints imposed by 3D motion parameters on the normal flow field, the possible space of solutions is gradually reduced. In the four modules that comprise the solution, constraints of increasing restriction are considered, culminating in testing every single normal flow value for its consistency with a set of motion parameters. The fact that motion is rigid defines geometric relations between certain values of the normal flow field. The selected values form patterns in the image plane that are dependent on only some of the motion parameters. These patterns, which are determined by the signs of the normal flow values, are searched for in order to find the axes of translation and rotation. The third rotational component is computed from normal flow vectors that are only due to rotational motion. Finally, by looking at the complete data set, all solutions that cannot give rise to the given normal flow field are discarded from the solution space.Research supported in part by NSF (Grant IRI-90-57934), ONR (Contract N00014-93-1-0257) and ARPA (Order No. 8459).
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