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The eignespace methhod for rigid motion recovery from less than eight point correspondences

机译:刚性运动恢复的EIGenspace方法从少于八点对应

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摘要

In this paper we ropose a new method for the estimation of rigid motion from two monocular images when less than eight point corresponences are available. The motion parameters are found using the essential matrix. By employing proviously unused constraints on essential matrix, we show that it can be estimated through the minimisation of a two-dimensional cost function defined over the space of all possible directions of translation. The new formulation is easier to understand and implement than previously proposed approaches, and has a low computational cost. The algorithm has been evaluated on synthetic data. Our experiments show that that the new method is capable of finding all solutions and that choice of initial state is not critical.
机译:在本文中,当不到八点的可用性时,我们撕裂了一种估计从两个单眼图像的刚性运动的新方法。使用基本矩阵找到运动参数。通过在基本矩阵上采用极致未使用的约束,我们表明可以通过最小化在所有可能的翻译方向的空间上定义的二维成本函数的最小化。新的配方比以前提出的方法更容易理解和实施,计算成本低。算法已在合成数据上进行评估。我们的实验表明,新方法能够找到所有解决方案,并且初始状态的选择并不重要。

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