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Two Separate Circles With Same-Radius: Projective Geometric Properties and Applicability in Camera Calibration

机译:两个独立的圆圈,具有相同半径:投影几何属性和相机校准中的适用性

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摘要

In the domain of computer vision, camera calibration is a key step in recovering the two-dimensional Euclidean structure. Circles are considered important image features similar to points, lines, and conics. In this paper, a novel linear calibration method is proposed using two separate same-radius (SSR) circles as the calibration pattern. We show that the distinct pair of dual circles encodes three lines, two of which are parallel to each other and perpendicular to the remaining line. When any two coplanar or parallel circles degenerate to SSR circles, a solution can be found to recover another pair of parallel lines based on the geometric properties of the SSR circles. Using the vanishing points obtained as the key helper for determining the imaged circular points and the orthogonal vanishing points, we deduce the constraints on the image of the absolute conic (IAC) and then employ it for complete camera calibration. Furthermore, a closed-form solution for the extrinsic parameters can be obtained based on the projective invariance of the conic dual to the circular points. Evaluations based on simulated and real data confirmed the effectiveness and feasibility of the proposed algorithms.
机译:在计算机视觉域中,相机校准是恢复二维欧几里德结构的关键步骤。圆圈被认为是类似于点,线条和锥体的重要图像特征。在本文中,使用两个独立的相同半径(SSR)圆作为校准模式提出了一种新的线性校准方法。我们表明,不同的双圆圈编码三条线,其中两个彼此平行并垂直于剩余线。当任何两个共面或并联圆圈退化到SSR圈时,可以发现一个解决方案基于SSR圈的几何属性来恢复另一对并行线。使用获得作为钥匙助助剂获得的消失点来确定成像圆点和正交消失点,我们推断了绝对圆锥(IAC)的图像上的约束,然后使用它以完成完整的相机校准。此外,可以基于圆锥双点的圆锥形点的投射不变性获得用于外部参数的闭合溶液。基于模拟和实数据的评估证实了所提出的算法的有效性和可行性。

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