The accuracy of camera calibration depends significantly on the control point detection which customarily subjects to image noise, distortion and resolution. This paper uses concentric circle grids as the calibration pattern and accordingly proposes a robust and accurate control point detection method for camera calibration. Each set of concentric circles on the grids pattern consists of multiple circles whose radii decrease progressively. The geometric structure of multi-hierarchies can not only robustly extract control points from complicated scenarios but also build a voting scheme to avoid numerical instability resulting from the estimation of projected centers. According to the common self-polar triangle of concentric circles and the local sub-pixel edge detection algorithm, we efficiently estimated sub-pixel coordinates of control points under projective transformation. Simulations and real experiments were conducted to demonstrate that the performance of calibration using concentric circle grids is superior to the popular grid patterns with respect to the image noise, distortion and resolution.

摄像机校准的准确性很大程度上取决于控制点检测，该检测点通常会受到图像噪声，失真和分辨率的影响。本文使用同心圆网格作为校准图案，因此提出了一种鲁棒且准确的相机校准控制点检测方法。网格图案上的每组同心圆由半径逐渐减小的多个圆组成。多层次结构的几何结构不仅可以从复杂的场景中稳健地提取控制点，而且还可以构建投票方案，从而避免因估计投影中心而导致的数值不稳定。根据同心圆的共同自极性三角形和局部亚像素边缘检测算法，我们有效地估计了投影变换下控制点的亚像素坐标。进行了仿真和真实实验，证明了在图像噪声，失真和分辨率方面，使用同心圆网格进行校准的性能优于流行的网格模式。