针对现有参数化Scheimpflug相机标定方法中初值确定过程复杂的问题,提出一种非参数化的基于广义成像模型的Scheimpflug相机标定方法。该模型将Scheimpflug相机看作一组像素和其对应的虚拟空间光线的集合,标定直接确定像素点与对应光线间的投影关系,能够避免参数化标定模型中复杂的初值确定过程。并基于不同视角下的标定图像中,同一像素点对应的多个位于不同局部坐标系下的控制点应在某一公共坐标系下共线的基本假设,提出基于棋盘格平面标定板的两步标定方法。利用多幅具有足够重叠度的标定图像进行粗标定,再将其他图像根据与已标定区域重叠度大小逐幅加入标定流程以完成初始标定;采用光束法平差算法对标定参数进行迭代优化。实验结果表明,所提方法操作灵活,正确有效,精度可靠。

To solve the problem of complicated initialization in existing parametric calibration models of the Scheimpflug camera, a new method based on general non-parametric imaging model is presented, which avoids the complicated initialization process and models the Scheimpflug camera as a set of image pixels and their associated projection rays in space. Thus, the calibration underlying general non-parametric imaging model simply refers to computation of the mapping between the pixels and the corresponding three-dimensional projection rays. Based on the assumption that multiple control points in respective local coordinate systems corresponding to same the pixel from different views should be collinear in a certain common coordinate system, a two-step calibration method using checkerboards is presented. A rough calibration is performed by using images of checkerboards with a sufficient overlap, and the rest image with largest overlap is iteratively added to calibration process to the complete the initial calibration. Then, a refinement of calibration is carried out through bundle adjustment. The real data experiments including calibration, reconstruction and pose estimation are performed, and the results demonstrate that the presented method is flexible, effective and accurate.