This paper presents an approach for calibrating omnidirectional single-viewpoint sensors using the central catadioptric projection properties of parallel lines. Single-viewpoint sensors are widely used in robot navigation and driverless cars; thus, a high degree of calibration accuracy is needed. In the unit viewing sphere model of central catadioptric cameras, a line in a three-dimensional space is projected to a great circle, resulting in the projections of a group of parallel lines intersecting only at the endpoints of the diameter of the great circle. Based on this property, when there are multiple groups of parallel lines, a group of orthogonal directions can be determined by a rectangle constructed by two groups of parallel lines in different directions. When there is a single group of parallel lines in space, the diameter and tangents at their endpoints determine a group of orthogonal directions for the plane containing the great circle. The intrinsic parameters of the camera can be obtained from the orthogonal vanishing points in the central catadioptric image plane. An optimization algorithm for line image fitting based on the properties of antipodal points is proposed. The performance of the algorithm is verified using simulated setups. Our calibration method was validated though simulations and real experiments with a catadioptric camera.

中文翻译：

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多组平行线的中心反射折射相机标定方法及其特性

本文提出了一种使用平行线的中心反射折射投影特性校准全向单视点传感器的方法。单视点传感器广泛应用于机器人导航和无人驾驶汽车；因此，需要高度的校准精度。在中央折反射相机的单位视球模型中，将三维空间中的一条线投影到一个大圆上，从而得到一组仅在大圆直径端点处相交的平行线的投影。基于这一性质，当存在多组平行线时，一组正交方向可以由两组不同方向的平行线构成的矩形确定。当空间中只有一组平行线时，端点处的直径和切线确定了包含大圆的平面的一组正交方向。相机的内在参数可以从中心反射折射图像平面中的正交消失点获得。提出了一种基于对映点特性的线图像拟合优化算法。使用模拟设置验证算法的性能。我们的校准方法通过反射折射相机的模拟和真实实验得到了验证。提出了一种基于对映点特性的线图像拟合优化算法。使用模拟设置验证算法的性能。我们的校准方法通过反射折射相机的模拟和真实实验得到了验证。提出了一种基于对映点特性的线图像拟合优化算法。使用模拟设置验证算法的性能。我们的校准方法通过反射折射相机的模拟和真实实验得到了验证。