Camera Calibration Based on Mirror Reflections
Camera Calibration Based on Mirror Reflections
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发表时间：
2018
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通讯作者：
Kosuke Takahashi
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作者：
Kosuke Takahashi
本文讨论了使用镜面反射来校准相机。摄像机标定是分析三维空间和二维图像之间几何和辐射关系的一项重要技术。大多数传统的相机校准方法都基于一个基本假设：相机可以直接观察已知几何形状的参考物体。然而，在某些情况下，这种假设在实际场景中并不成立。在这种情况下，相机校准的一种方法是使用“镜子”作为支持设备。镜像生成一个虚拟的参考对象，该对象可以用少量参数表示。另外，从虚拟视点看，反射物体的二维投影等于已知参考物体的二维投影。本文利用这些特征，解决了几何摄像机标定的两个难题；第一个挑战是当没有已知的参考对象时，相机的内在校准；第二个挑战是当相机由于成像系统的物理约束而不能直接观察到已知的参考对象时，相机的外在校准。为了解决这些问题，该算法引入了新的约束，即万花筒投影约束和正交约束，这些约束与镜面反射相结合。综合数据和实际数据的评价结果表明，该算法具有较好的鲁棒性。
: This paper addresses the use of mirror reflections for camera calibration. Camera calibration is an essential technique for analyzing the geometric and radiometric relationship between a 3D space and a 2D image. Most conventional camera calibration methods are based on a fundamental assumption: a camera can directly observe a reference object of known geometry . However, there are cases in which this assumption does not hold in practical scenarios. One approach to camera calibration in such cases is the use of a “mirror” as a supporting device. A mirror generates a virtual reference object that can be expressed using a small number of parameters. In addition, the 2D projection of the reflection object is equal to that of the known reference object from the virtual viewpoint. This paper utilizes these features and tackles two challenges of the geometric camera calibration; the first challenge is the intrinsic camera calibration when a known reference object is not available and the second challenge is the extrinsic camera calibra- tion when the camera cannot directly observe a known reference object due to a physical constraint on the imaging system. The proposed algorithms introduce novel constraints, kaleidoscopic projection constraint and orthogonality constraint , which are hold with the mirror reflections for solving these problems. Evaluations with synthesized and real data demonstrates that the proposed algorithms can work properly and report the robustness of it in comparison with conventional methods.