Zhedong Zheng

Zhedong Zheng

Asst. Prof. @ UMacau
IEEE Senior Member

Bayesian query expansion for multi-camera person re-identification

Authors: yutian-linYutian Lin, Zhedong Zheng, Hong Zhang, Chenqiang Gao, yi-yangYi Yang

Published in Pattern Recognition Letters (PRL), 2020

Recommended citation: Yutian Lin, Zhedong Zheng, Hong Zhang, Chenqiang Gao, Yi Yang, "Bayesian query expansion for multi-camera person re-identification." Pattern Recognition Letters, 2020. DOI: 10.1016/j.patrec.2018.06.009
Download PDF: https://zdzheng.xyz/files/2020/PRLetter18.pdf

Abstract: Person re-identification (re-ID) is challenging because pedestrians may exhibit distinct appearance under different cameras. Given a query image, previous methods usually output the person retrieval results directly, which may perform badly due to the limited information provided by the single query image. To mine more query information, we add an expansion step to post-process the initial ranking list. The intuition is that a true match in the gallery may be difficult to be found by the query alone, but it can be easily retrieved by other true matches in the initial ranking list. In this paper, we propose the Bayesian Query Expansion (BQE) method to generate a new query with information from the initial ranking list. The Bayesian model is used to predict true matches in the gallery. We apply pooling on the features of these “true matches” to get a single vector, i.e. , the expanded new query, with which the retrieval process is performed again to obtain the final results. We evaluate BQE with various feature extraction methods and distance metric learning methods on four large-scale re-ID datasets. We observe consistent improvement over all the baselines and report competitive performances compared with the state-of-the- art results.

Keywords:

camera person identification multi camera person camera person object re-identification content-based retrieval person re-id person retrieval person search 
@article{lin2020bayesian,
author = "Lin, Yutian and Zheng, Zhedong and Zhang, Hong and Gao, Chenqiang and Yang, Yi",
doi = "10.1016/j.patrec.2018.06.009",
title = "Bayesian query expansion for multi-camera person re-identification",
abstract = "Person re-identification (re-ID) is challenging because pedestrians may exhibit distinct appearance under different cameras. Given a query image, previous methods usually output the person retrieval results directly, which may perform badly due to the limited information provided by the single query image. To mine more query information, we add an expansion step to post-process the initial ranking list. The intuition is that a true match in the gallery may be difficult to be found by the query alone, but it can be easily retrieved by other true matches in the initial ranking list. In this paper, we propose the Bayesian Query Expansion (BQE) method to generate a new query with information from the initial ranking list. The Bayesian model is used to predict true matches in the gallery. We apply pooling on the features of these “true matches” to get a single vector, i.e. , the expanded new query, with which the retrieval process is performed again to obtain the final results. We evaluate BQE with various feature extraction methods and distance metric learning methods on four large-scale re-ID datasets. We observe consistent improvement over all the baselines and report competitive performances compared with the state-of-the- art results.",
journal = "Pattern Recognition Letters",
volume = "130",
pages = "284--292",
year = "2020",
publisher = "Elsevier",
url = "https://zdzheng.xyz/files/2020/PRLetter18.pdf" }