多摄像机系统广泛应用于文化创意产业,其高精度标定是迫切需要解决的一个关键问题.新近出现的摄像机一维标定方法能够克服标定物自身遮挡,特别适合标定多摄像机系统.然而,现有的摄像机一维标定研究主要集中在降低一维标定物的运动约束,而标定精度较低的问题未受到应有的关注.本文提出一种基于变量含异质噪声(Heteroscedastic error-in-variables,HEIV)模型的高精度摄像机一维标定方法.首先,推导出摄像机一维标定的计算模型;其次,利用该计算模型详细分析了一维标定中的噪声,得出摄像机一维标定可以视为一个HEIV问题的结论;最后给出了基于HEIV模型的摄像机一维标定算法.与现有的算法相比,该方法可以显著改善一维标定的精度,并且受初始值影响小,收敛速度快.实验结果验证了该方法的正确性和可行性.
Accurate camera calibration is a pre-requirement for widespread applications of the multi-camera system in cultural and creative industry. The newly emerging one-dimensional calibration is very suitable for multi-camera systems since one-dimensional objects are out of self-occlusions. However, the progress in one-dimensional calibration mainly focuses on reducing restrictions on the movement of one-dimensional objects, and the calibration accuracy still needs to be improved. In this paper, an accurate algorithm for one-dimensional calibration based on the heteroscedastic error-in-variables (HEIV) model is proposed. Firstly, a computational model of one-dimensional calibration is derived. Secondly, noises in one-dimensional calibration are analyzed in detail using this computational model, and we draw a conclusion that one-dimensional calibration can be seen as an HEIV problem. Finally, the proposed algorithm is elaborated. This algorithm has the advantages of high accuracy, rapid conve