The development of stereo-digital image correlation (stereo-DIC) enables the application of vision-based technique that uses digital cameras to the deformation measurement of materials and structures. Compared with traditional contact measurements, the stereo-DIC technique allows for non-contact measurement, has a non-intrusive characteristic, and can obtain full-field deformation information. In this paper, a speckle-based calibration method is developed to calibrate the stereo-DIC system when the system is applied for deformation measurement of large engineering components. By combining speckle analysis with the classical relative orientation algorithm, relative rotation and translation between cameras can be calibrated based on analysis of experimental speckle images. For validation, the strain fields of a four-point bending beam and an axially loaded concrete column were determined by the proposed calibration method and stereovision measurement. As a practical application, the proposed calibration method was applied for strain measurement of a ductile iron cylindrical vessel in the drop test. The measured results verify that the proposed calibration method is effective for deformation measurement of large engineering components.

The accuracy of strain measurement using a common optical extensometer with two-dimensional (2D) digital image correlation (DIC) is not sufficient for experimental applications due to the effect of out-of-plane motion. Although three-dimensional (3D) DIC can measure all three components of displacement without introducing in-plane displacement errors, 3D-DIC requires the stringent synchronization between two digital cameras and requires complicated system calibration of binocular stereovision, which makes the measurement rather inconvenient. To solve the problems described above, this paper proposes a self-calibration single-lens 3D video extensometer for non-contact, non-destructive and high-accuracy strain measurement. In the established video extensometer, a single-lens 3D imaging system with a prism and two mirrors is constructed to acquire stereo images of the test sample surface, so the problems of synchronization and out-of-plane displacement can be solved easily. Moreover, a speckle-based self-calibration method which calibrates the single-lens stereo system using the reference speckle image of the specimen instead of the calibration targets is proposed, which will make the system more convenient to be used without complicated calibration. Furthermore, an efficient and robust inverse compositional Gauss-Newton algorithm combined with a robust stereo matching stage is employed to achieve high-accuracy and real-time subset-based stereo matching. Tensile tests of an Al-alloy specimen were performed to demonstrate the feasibility and effectiveness of the proposed self-calibration single-lens 3D video extensometer.

In this paper, an extrinsic calibration method for a non-overlapping camera network is presented based on close-range photogrammetry. The method does not require calibration targets or the cameras to be moved. The visual sensors are relatively motionless and do not see the same area at the same time. The proposed method combines the multiple cameras using some arbitrarily distributed encoded targets. The calibration procedure consists of three steps: reconstructing the three-dimensional (3D) coordinates of the encoded targets using a hand-held digital camera, performing the intrinsic calibration of the camera network, and calibrating the extrinsic parameters of each camera with only one image. A series of experiments, including 3D reconstruction, rotation, and translation, are employed to validate the proposed approach. The results show that the relative error for the 3D reconstruction is smaller than 0.003%, the relative errors of both rotation and translation are less than 0.066%, and the re-projection error is only 0.09 pixels.