Qualitative egomotion
作者:Cornelia Fermüller, Yiannis Aloimonos
摘要
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.
论文关键词:Computer Vision, Image Plane, Solution Space, Rotational Motion, Flow Measurement
论文评审过程:
论文官网地址:https://doi.org/10.1007/BF01450848