Deep Subspace Methods-Pattern Recognition using Hierarchical Structure of Linear Subspaces

摘要

We introduce an new geodesic distance between images. This distance is defined as the Wasserstein distance between contribution ratios of eigenvalues. For the computation of eigenvectors, we use tensor decomposition. Using this geodesic distance, we explore hierarchical structure of linear subspaces of images.