Person Re-Identification Using A Patch-Based Appearance Model

Person re-identification is the process of recognizing a person across a network of cameras with non-overlapping fields of view. In this paper we present an unsupervised multi-shot approach based on a patch-based dynamic appearance model. We use deformable graph matching for person re-identification using histograms of color and texture as features of nodes. Each graph model spans multiple images and each node is a local patch in the shape of a rectangle. We evaluate our proposed method on publicly available PRID 2011 and iLIDS-VID databases.