Triangulation
Triangulation
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DOI：
10.1006/cviu.1997.0547
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发表时间：
1997-11-01
影响因子：
4.5
通讯作者：
Sturm, P
中科院分区：
文献类型：
--
作者：
Hartley, RI;Sturm, P
在本文中，我们考虑的问题是，给定一个点在空间中的位置，在已知的校准和姿势的相机拍摄的两幅图像中，这个过程需要两个已知射线在空间中的相交，通常被称为三角测量。在没有噪声的情况下，这个问题是不重要的，当存在噪声时，两条射线通常不会相交，在这种情况下，需要找到最佳交点，这个问题在仿射和射影重建中尤其关键，在这些重建中，没有关于物体空间的有意义的度量信息，需要找到一种对空间射影变换不变的三角剖分方法。本文通过假设图像坐标扰动的高斯噪声模型来解决这一问题，从而将三角剖分问题表述为最小二乘最小化问题。本文给出了一个求全局最小值的非迭代解。结果表明，在某些构型下，会出现局部最小值，而新方法避免了这种情况的发生。(C) 1997学术出版社。
In this paper, we consider the problem of finding the position of a point in space given its position in two images taken with cameras with known calibration and pose, This process requires the intersection of two known rays in space and is commonly known as triangulation. In the absence of noise, this problem is trivial, When noise is present, the two rays will not generally meet, in which case it is necessary to find the best point of intersection, This problem is especially critical in affine and projective reconstruction in which there is no meaningful metric information about the object space, It is desirable to find a triangulation method that is invariant to projective transformations of space, This paper solves that problem by assuming a Gaussian noise model for perturbation of the image coordinates, The triangulation problem may then be formulated as a least-squares minimization problem, In this paper a noniterative solution is given that finds the global minimum, It is shown that in certain configurations, local minima occur, which are avoided by the new method, Extensive comparisons of the new method with several other methods show that it consistently gives superior results. (C) 1997 Academic Press.