Liang Sixin, Zhao Yue
Appl Opt. 2020 Jun 10;59(17):5167-5178. doi: 10.1364/AO.388109.
Computer vision camera calibration is widely performed using parallel circles. Various cases of two coplanar circles are algebraically explained, proving that the common pole is located at the line at infinity for all relative positions, and the corresponding polar passes through the centers of the two circles. The two common poles of the two coplanar circles are the points at infinity when concentric; one common pole of the two coplanar circles is a point at infinity when nonconcentric. Accordingly, the vanishing line can be obtained by using the common pole-polar properties of two groups of two coplanar circles, and the camera's intrinsic parameters are solved according to the constraints between the image of the circular points and the imaged absolute conic. The camera calibration can be solved using only three images of two coplanar circles. Simulation and experiments verify that the proposed algorithms are effective.
计算机视觉相机校准广泛使用平行圆来进行。代数解释了两个共面圆的各种情况,证明对于所有相对位置,公共极点位于无穷远直线上,并且相应的极线通过两个圆的圆心。当两个共面圆同心时,它们的两个公共极点是无穷远点;当两个共面圆不同心时,它们的两个公共极点中的一个是无穷远点。因此,可以利用两组两个共面圆的公共极点 - 极线特性来获得消失线,并根据圆点图像与成像绝对二次曲线之间的约束来求解相机的内参。仅使用两个共面圆的三张图像就可以求解相机校准。仿真和实验验证了所提出的算法是有效的。