An ordered-patch-based image classification approach on the image Grassmannian manifold.

This paper presents an ordered-patch-based image classification framework integrating the image Grassmannian manifold to address handwritten digit recognition, face recognition, and scene recognition problems. Typical image classification methods explore image appearances without considering the spatial causality among distinctive domains in an image. To address the issue, we introduce an ordered-patch-based image representation and use the autoregressive moving average (ARMA) model to characterize the representation.