Auto-calibration and real-time external parameter correction for stereo digital image correlation

Calibrating stereo digital image correlation (stereo-DIC) is crucial for 3D deformation measurements. Existing stereo-DIC calibration methods mainly rely on a well-made planar target with additional specific coding to perform pre-calibration. In this paper, a new method is proposed to calibrate a stereo-DIC system automatically with feature correspondences in an unconstrained scene. In contrast to traditional methods, the proposed method is scale-independent and does not require assumptions such as planarity. More importantly, it is capable of correcting disturbed external parameters in real time. With inverse depth parameterization, a stereo-DIC system can be effectively calibrated by a carefully designed bundle adjustment framework. Subsequently, a fast correction strategy based on massive-point subset tracking is derived to recalibrate the disturbed stereo-DIC system. The proposed method overcomes the predicament of reduced measurement accuracy due to the unavoidable disturbance of external parameters in dynamic deformation measurements. Experiments were conducted to verify the effectiveness of the proposed method.