Li Xiao, Li Wei, Yuan Xin'an, Yin XiaoKang, Ma Xin
School of Mechanical and Electrical Engineering, China University of Petroleum (East China), Huangdao, Qingdao 266580, China.
Polytechnic Institute, Purdue University, West Lafayette, IN 47907, USA.
Sensors (Basel). 2020 Oct 20;20(20):5934. doi: 10.3390/s20205934.
Lens distortion is closely related to the spatial position of depth of field (DoF), especially in close-range photography. The accurate characterization and precise calibration of DoF-dependent distortion are very important to improve the accuracy of close-range vision measurements. In this paper, to meet the need of short-distance and small-focal-length photography, a DoF-dependent and equal-partition based lens distortion modeling and calibration method is proposed. Firstly, considering the direction along the optical axis, a DoF-dependent yet focusing-state-independent distortion model is proposed. By this method, manual adjustment of the focus and zoom rings is avoided, thus eliminating human errors. Secondly, considering the direction perpendicular to the optical axis, to solve the problem of insufficient distortion representations caused by using only one set of coefficients, a 2D-to-3D equal-increment partitioning method for lens distortion is proposed. Accurate characterization of DoF-dependent distortion is thus realized by fusing the distortion partitioning method and the DoF distortion model. Lastly, a calibration control field is designed. After extracting line segments within a partition, the de-coupling calibration of distortion parameters and other camera model parameters is realized. Experiment results shows that the maximum/average projection and angular reconstruction errors of equal-increment partition based DoF distortion model are 0.11 pixels/0.05 pixels and 0.013°/0.011°, respectively. This demonstrates the validity of the lens distortion model and calibration method proposed in this paper.
镜头畸变与景深(DoF)的空间位置密切相关,尤其是在近距摄影中。准确表征和精确校准与景深相关的畸变对于提高近距视觉测量的精度非常重要。本文针对短距离和小焦距摄影的需求,提出了一种基于景深依赖和等分区的镜头畸变建模与校准方法。首先,考虑沿光轴方向,提出了一种与景深相关但与聚焦状态无关的畸变模型。通过这种方法,避免了手动调整对焦环和变焦环,从而消除了人为误差。其次,考虑垂直于光轴的方向,为解决仅使用一组系数导致的畸变表示不足的问题,提出了一种镜头畸变的二维到三维等增量分区方法。通过融合畸变分区方法和景深畸变模型,实现了对与景深相关的畸变的准确表征。最后,设计了一个校准控制场。在提取分区内的线段后,实现了畸变参数与其他相机模型参数的解耦校准。实验结果表明,基于等增量分区的景深畸变模型的最大/平均投影误差和角度重建误差分别为0.11像素/0.05像素和0.013°/0.011°。这证明了本文提出的镜头畸变模型和校准方法的有效性。