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基于立体视觉和多项式拟合的条纹投影轮廓术混合校准程序。

Hybrid calibration procedure for fringe projection profilometry based on stereo vision and polynomial fitting.

作者信息

Vargas Raúl, Marrugo Andres G, Zhang Song, Romero Lenny A

出版信息

Appl Opt. 2020 May 1;59(13):D163-D169. doi: 10.1364/AO.383602.

Abstract

The key to accurate 3D shape measurement in fringe projection profilometry (FPP) is the proper calibration of the measurement system. Current calibration techniques rely on phase-coordinate mapping (PCM) or back-projection stereo vision (SV) methods. PCM methods are cumbersome to implement as they require precise positioning of the calibration target relative to the FPP system, but they produce highly accurate measurements within the calibration volume. SV methods generally do not achieve the same accuracy level. However, the calibration is more flexible in that the calibration target can be arbitrarily positioned. In this work, we propose a hybrid calibration method that leverages the SV calibration approach using a PCM method to achieve higher accuracy. The method has the flexibility of SV methods, is robust to lens distortions, and has a simple relation between the recovered phase and the metric coordinates. Experimental results show that the proposed hybrid method outperforms the SV method in terms of accuracy and reconstruction time due to its low computational complexity.

摘要

条纹投影轮廓术(FPP)中精确三维形状测量的关键在于测量系统的正确校准。当前的校准技术依赖于相位坐标映射(PCM)或反向投影立体视觉(SV)方法。PCM方法实施起来很麻烦,因为它们需要校准目标相对于FPP系统的精确定位,但在校准体积内可产生高度精确的测量结果。SV方法通常达不到相同的精度水平。然而,校准更加灵活,因为校准目标可以任意定位。在这项工作中,我们提出了一种混合校准方法,该方法利用SV校准方法并结合PCM方法以实现更高的精度。该方法具有SV方法的灵活性,对镜头畸变具有鲁棒性,并且恢复的相位与度量坐标之间具有简单的关系。实验结果表明,由于计算复杂度低,所提出的混合方法在精度和重建时间方面优于SV方法。

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