Novelty Detection for Person Re-identification in an Open World

George Galanakis, Xenophon Zabulis, Antonis A. Argyros

2019

Abstract

A fundamental assumption in most contemporary person re-identification research, is that all query persons that need to be re-identified belong to a closed gallery of known persons, i.e., they have been observed and a representation of their appearance is available. For several real-world applications, this closed-world assumption does not hold, as image queries may contain people that the re-identification system has never observed before. In this work, we remove this constraining assumption. To do so, we introduce a novelty detection mechanism that decides whether a person in a query image exists in the gallery. The re-identification of persons existing in the gallery is easily achieved based on the persons representation employed by the novelty detection mechanism. The proposed method operates on a hybrid person descriptor that consists of both supervised (learnt) and unsupervised (hand-crafted) components. A series of experiments on public, state of the art datasets and in comparison with state of the art methods shows that the proposed approach is very accurate in identifying persons that have not been observed before and that this has a positive impact on re-identification accuracy.

Paper Citation

in Harvard Style

Galanakis G., Zabulis X. and Argyros A. (2019). Novelty Detection for Person Re-identification in an Open World. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 401-411. DOI: 10.5220/0007368304010411

in Bibtex Style

@conference{visapp19,
author={George Galanakis and Xenophon Zabulis and Antonis A. Argyros},
title={Novelty Detection for Person Re-identification in an Open World},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={401-411},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007368304010411},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Novelty Detection for Person Re-identification in an Open World
SN - 978-989-758-354-4
AU - Galanakis G.
AU - Zabulis X.
AU - Argyros A.
PY - 2019
SP - 401
EP - 411
DO - 10.5220/0007368304010411
PB - SciTePress