Path independent strategy is introduced into stereo digital image correlation, in which high accuracy is attained through the inverse compositional Gauss-Newton (IC-GN) algorithm with the second and the first order shape functions for stereo matching and temporal matching, respectively. To gain strong adaptibility to large and complex deformation or considerable parallax betweent the two views, two robust methods are developped to estimate the initial guess for the iterative IC-GN algorithm. One is aided by scale invariant feature transform (SIFT) features and the other is aided by epipolar constraint. Powered by parallel computing on GPU, the proposed stereo DIC demonstrates high computation efficiency. Real-time stereo DIC is realized and used to measure the large deformation at common video recording rate (∼24 fps) with high ananlysis resolution (∼6300 points of interest in region of interest).

路径无关策略被引入立体数字图像相关中，其中通过逆合成高斯-牛顿（IC-GN）算法与立体匹配和时间匹配的二阶和一阶形状函数分别获得高精度。为了对两个视图之间的大而复杂的变形或相当大的视差具有很强的适应性，开发了两种稳健的方法来估计迭代 IC-GN 算法的初始猜测。一个由尺度不变特征变换 (SIFT) 特征辅助，另一个由对极约束辅助。由 GPU 上的并行计算提供支持，所提出的立体 DIC 显示出高计算效率。