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Self-calibration of Cameras with Euclidean Image Plane in Case of Two Views and Known Relative Rotation Angle

机译:具有两种视图和已知相对旋转角度的欧几里得像平面相机的自校准

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The internal calibration of a pinhole camera is given by five parameters that are combined into an upper-triangular 3×3 calibration matrix. If the skew parameter is zero and the aspect ratio is equal to one, then the camera is said to have Euclidean image plane. In this paper, we propose a non-iterative self-calibration algorithm for a camera with Euclidean image plane in case the remaining three internal parameters - the focal length and the principal point coordinates - are fixed but unknown. The algorithm requires a set of N ≥ 7 point correspondences in two views and also the measured relative rotation angle between the views. We show that the problem generically has six solutions (including complex ones). The algorithm has been implemented and tested both on synthetic data and on publicly available real dataset. The experiments demonstrate that the method is correct, numerically stable and robust.
机译:针孔摄像机的内部校准由五个参数组合在一起,这些参数组合成一个上三角3×3校准矩阵。如果偏斜参数为零,并且纵横比等于1,则表示摄影机具有欧几里得像平面。在本文中,如果剩余的三个内部参数(焦距和主点坐标)是固定的,但未知,我们将为具有欧几里得像面的相机提出一种非迭代的自校准算法。该算法需要在两个视图中具有一组N≥7个点对应关系,并且还需要在这些视图之间测得的相对旋转角度。我们证明该问题通常有六个解决方案(包括复杂的解决方案)。该算法已在合成数据和可公开获得的真实数据集上实施和测试。实验表明,该方法是正确的,数值稳定的和鲁棒的。

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