Abstract Calibration of a stereo vision system is essential for three-dimensional shape and deformation measurements. Although the target-based calibration technique is a good solution, it comes with limitations in a large field of view (FOV) measurement due to the target size and difficulties in operation. In this paper, a method using the inertial measurement unit (IMU) has been proposed to calibrate stereo vision systems for large-scale measurements. The prerequisite for this method is to calibrate the camera intrinsic parameters in advance. With the alignment of IMU sensor with the camera, the relative rotation between the two cameras can be determined through coordinate transform. An angular differential method has been developed to improve accuracy in determining the yaw angle. After the epipolar geometry is constructed upon stereo scene correspondences, the translation vector can be obtained by solving a set of linear equations, since the intrinsic parameters and the relative rotation are predefined. The proposed method does not require any known calibration target, leading to easy operation in practice. Two laboratory experiments are presented to demonstrate the use of the method. The experimental results show that the accuracy of the proposed method is comparable to that resulted from the well-known Zhang's method, and it can also be applied to measurement with a large FOV.

中文翻译：

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惯性测量单元辅助立体视觉系统外参数标定

摘要 立体视觉系统的校准对于三维形状和变形测量至关重要。虽然基于目标的校准技术是一个很好的解决方案，但由于目标尺寸和操作困难，它在大视场 (FOV) 测量中存在局限性。在本文中，提出了一种使用惯性测量单元 (IMU) 来校准立体视觉系统以进行大规模测量的方法。这种方法的前提是事先校准好相机内参。通过IMU传感器与相机的对准，可以通过坐标变换来确定两个相机之间的相对旋转。已经开发了一种角微分方法来提高确定偏航角的精度。在立体场景对应上构建对极几何之后，由于内在参数和相对旋转是预定义的，因此可以通过求解一组线性方程来获得平移向量。所提出的方法不需要任何已知的校准目标，从而在实践中易于操作。提供了两个实验室实验来演示该方法的使用。实验结果表明，该方法的精度与著名的张氏方法的精度相当，也可以应用于大视场的测量。从而在实践中易于操作。提供了两个实验室实验来演示该方法的使用。实验结果表明，该方法的精度与著名的张氏方法的精度相当，也可以应用于大视场的测量。从而在实践中易于操作。提供了两个实验室实验来演示该方法的使用。实验结果表明，该方法的精度与著名的张氏方法的精度相当，也可以应用于大视场的测量。