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The Six Point Algorithm Revisited

机译:再谈六点算法

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摘要

This paper presents an algorithm for estimating camera focal length from tentative matches in a pair of images, which works robustly in practical situations such as automatic computation of structure and camera motion from unknown photographs, e.g. from the web or from various instruments mounted on a vehicle. We extend the standard 6-pt algorithm based on the observations: (i) the quality of the estimation of this algorithm is strongly correlated with the ratio of the singular values of the essential matrix computed from inliers, which is calibrated by using the estimated focal length, returned by RANSAC and (ii) the reprojection error of the affine camera model, fit to the inliers, predicts the uncertainty in the estimated focal length. Furthermore, for scenes with dominant plane we propose a novel algorithm calculating relative orientation and unknown focal length given a plane homography and a single off the plane point correspondence. The performance of the proposed algorithm is demonstrated on a set of real images having different focal lengths.
机译:本文提出了一种根据一对图像中的临时匹配估计相机焦距的算法,该算法在实际情况下表现出色,例如自动计算结构和根据未知照片拍摄的相机运动。来自网络或安装在车辆上的各种仪器。我们基于以下观察结果扩展标准的6点算法:(i)该算法的估计质量与从Inliers计算出的基本矩阵的奇异值之比密切相关,该奇异值可通过使用估计的焦点进行校准由RANSAC返回的长度,以及(ii)仿射相机模型的重投影误差(适合于原点),可预测估计焦距的不确定性。此外,对于具有优势平面的场景,我们提出了一种新颖的算法,该算法可在给定平面单应性和单个平面外点对应的情况下计算相对方向和未知焦距。在具有不同焦距的一组真实图像上证明了所提出算法的性能。

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