Multimodal person re-identification using RGB-D sensors and a transient identification database

Abstract

This paper describes a system for person re-identification using RGB-D sensors. The system covers the full flow, from detection of subjects, over contour extraction, to re-identification using soft biometrics. The biometrics in question are part-based color histograms and the subjects height. Subjects are added to a transient database and re-identified based on the distance between recorded biometrics and the currently measured metrics. The system works on live video and requires no collaboration from the subjects. The system achieves a 68% re-identification rate with no wrong re-identifications, a result that compares favorable with commercial systems as well as other very recent multimodal re-identification systems.