A fast subspace algorithm for recovering rigid motion

Allan D. Jepson, D. J. Heeger
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引用次数: 66

Abstract

The image motion field for an observer moving through a static environment depends on the observer's translational and rotational velocities along with the distances to surface points. Given such a motion field as input the authors present a new algorithm for computing the observer's motion and the depth structure of the scene. The approach is a further development of sub-space methods. This class of methods involve splitting the equations describing the motion field into separate equations for the observer's translational direction, the rotational velocity and the relative depths. The resulting equations can then be solved successively, beginning with the equations for the translational direction. The authors show how this first step can be simplified considerably. The consequence is that the observer's velocity and the relative depths to points in the scene can all be recovered by successively solving three linear problems.<>
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一种快速恢复刚性运动的子空间算法
在静态环境中运动的观察者的像移场取决于观察者的平移速度和旋转速度以及到表面点的距离。在给定运动场作为输入的情况下,提出了一种计算观察者运动和场景深度结构的新算法。该方法是子空间方法的进一步发展。这类方法包括将描述运动场的方程分解为观察者的平移方向、旋转速度和相对深度的单独方程。由此得到的方程可以依次求解,从平动方向的方程开始。作者展示了如何将这第一步大大简化。结果是,观察者的速度和场景中点的相对深度都可以通过连续求解三个线性问题来恢复。
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