| Title |
A novel person re-identification network to address low-resolution problem in smart city context |
| ID_Doc |
39020 |
| Authors |
Yaqoob, I; Hassan, MU; Niu, DM; Zhao, XY; Hameed, IA; Ul Hassan, S |
| Title |
A novel person re-identification network to address low-resolution problem in smart city context |
| Year |
2023 |
| Published |
Ict Express, 9, 5 |
| DOI |
10.1016/j.icte.2022.07.010 |
| Abstract |
We argue that accurate person re-identification is a vital problem for urban public monitoring systems in the smart city context. Since images captured from different cameras have arbitrary resolutions resulting in resolution mismatch, this work proposes a model that takes arbitrary images and converts them to a pre-defined fixed resolution. The model then passes the images to a super-resolution network, producing high-resolution images. We employ a feedback network to generate more realistic super-resolution images, which are fed to the re-identification network to acquire a unique descriptor to disclose the person's identity. We outperformed in all measures against other state-of-the-art methods. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Author Keywords |
Person re-identification; High resolution; Smart cities; Deep learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001102284800001 |
| WoS Category |
Computer Science, Information Systems; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
https://doi.org/10.1016/j.icte.2022.07.010
|