School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
Opt Lett. 2013 May 1;38(9):1446-8. doi: 10.1364/OL.38.001446.
The calibration of camera with intrinsic and extrinsic parameters is a procedure of significance in current imaging-based optical metrology. Improvement at two aspects, feature detection and overall optimization, are investigated here by using an active phase target and statistically constrained bundle adjustment (SCBA). From the observations in experiment and simulation, the feature detection can be enhanced by "virtual defocusing" and windowed polynomial fitting if sinusoidal fringe patterns are used as the active phase target. SCBA can be applied to avoid the difficult measurement of the active target. As a typical calibration result in our experiment, the root mean square of reprojection error can be reduced to 0.0067 pixels with the proposed method.
相机内参和外参标定在当前基于成像的光学测量中具有重要意义。本文通过使用主动相位目标和统计约束束调整(SCBA),从特征检测和整体优化两个方面进行了改进。通过实验和模拟中的观察,如果将正弦条纹图案用作主动相位目标,则可以通过“虚拟散焦”和窗口多项式拟合来增强特征检测。可以应用 SCBA 来避免主动目标的困难测量。作为我们实验中的一个典型标定结果,所提出的方法可以将重投影误差的均方根降低到 0.0067 像素。