Person re‐identification with discriminatively trained viewpoint invariant orthogonal dictionaries

Abstract

A novel and efficient method for person re-identification based on orthogonal dictionary learning is proposed. The orthogonal dictionary exhibits extraordinary discriminative power than the classical dictionary learning. It is learned with the help of convex optimisation and customised trace optimisation. The approach has been evaluated against current methods on a benchmark dataset and can reach outstanding performance.