面向工业检测的光场相机快速标定研究

Fast Light Field Camera Calibration for Industrial Inspection

由于光场数据量大,现有光场相机标定算法存在速度慢、无法快速校准工业检测中光场相机的参数变化、降低工业检测效率的问题。该文基于稀疏光场成像模型优化光场数据,提出光场相机快速标定算法。该算法以清晰度作为图像质量评价指标,从光场数据中选取高质量、具有代表性的稀疏视图,构建稀疏光场;接着利用稀疏光场求解相机参数初值并优化,得到最佳参数。实验结果表明,与现有最优标定算法相比,该方法不仅提高平均标定速度70%以上,在现有5个数据集的平均标定时间从101.27 s减少到30.99 s,而且保持标定精度在最优水平,在公开数据集PlenCalCVPR2013DatasetA的标定误差仅为0.0714 mm。

To solve the problem of the slow speed of the existing light field camera calibration algorithm,which makes it unable to quickly calibrate camera parameter changes in industrial inspection and reduce the efficiency of industrial inspection.A fast calibration algorithm for light field cameras is proposed.It selects high-quality,representative sparse views from the light field data based on image clarity,and establishes the sparse light field,which is used for calibration.Compared with the existing optimal approach,the proposed method not only increases the average calibration speed by more than 70%,reducing the average calibration time from 101.27 s to 30.99 s in the existing five datasets,but also maintains the calibration accuracy at the optimal level.The calibration error in the public dataset PlenCalCVPR2013DatasetA is only 0.0714 mm.