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Fast and Robust Numerical Solutions to Minimal Problems for Cameras with Radial Distortion

机译:具有径向失真的相机的最小问题快速和强大的数值解决方案

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A number of minimal problems of structure from motion for cameras with radial distortion have recently been studied and solved in some cases. These problems are known to be numerically very challenging and in several cases there exist no known practical algorithm yielding solutions in floating point arithmetic. We make some crucial observations concerning the floating point implementation of Grobner basis computations and use these new insights to formulate fast and stable algorithms for two minimal problems with radial distortion previously solved in exact rational arithmetic only: (i) simultaneous estimation of essential matrix and a common radial distortion parameter for two partially calibrated views and six image point correspondences and (ii) estimation of fundamental matrix and two different radial distortion parameters for two uncalibrated views and nine image point correspondences. We demonstrate on simulated and real experiments that these two problems can be efficiently solved in floating point arithmetic.
机译:在某些情况下,最近研究并解决了具有径向畸变的相机运动的许多结构问题。已知这些问题在数字上非常具有挑战性,并且在几个情况下,在浮点算术中没有任何已知的实用算法产生解。我们对Grobner基础计算的浮点实施进行了一些重要观察,并利用这些新的见解来制定快速和稳定的算法,以实现两个最小的问题,其径向失真仅在精确的算术中解决:(i)同时估计基本矩阵和一个用于两个部分校准视图的常见径向失真参数和六个图像点对应关系和(ii)基本矩阵的估计和两个未校准视图和九个图像点对应的两个不同的径向失真参数。我们展示了模拟和实验实验,即在浮点算术中可以有效地解决这两个问题。

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