Shear Stress Using Face Recognition

This code uses a technique originally developed for facial recognition to describe shear stress distributions in open channel flow. In this approach, a synthetic database of images representing normalized shear stress distributions is formed from the training data set using recurrence plot analysis. A face recognition algorithm is then employed to synthesize the recurrence plots and transform the original database into short-dimension vectors containing similarity weights proportional to the principal components of the distribution of images. These vectors capture the intrinsic properties of the boundary shear stress distribution of the cases in the training set, and are sensitive to variations of the corresponding hydraulic parameters. The process of transforming one-dimensional data series into vectors of weights is reversible, and therefore, shear stress distributions for unseen cases can be predicted.