Marco San Biagio

Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification

This paper presents a novel framework for visual object recognition using infinite-dimensional covariance operators of input features, in the paradigm of kernel methods on infinite-dimensional Riemannian manifolds. Our formulation provides a rich representation of image features by exploiting their…