Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images
| dc.contributor.author | Baisa, Nathanael L. | |
| dc.date.acceptance | 2024-06-15 | |
| dc.date.accessioned | 2024-07-09T13:55:50Z | |
| dc.date.available | 2024-07-09T13:55:50Z | |
| dc.date.issued | 2024-06-27 | |
| dc.description | The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. | |
| dc.description.abstract | Learning representative, robust and discriminative information from images is essential for effective person re-identification (Re-Id). In this paper, we propose a compound approach for end-to-end discriminative deep feature learning for person Re-Id based on both body and hand images. We carefully design the Local-Aware Global Attention Network (LAGA-Net), a multi-branch deep network architecture consisting of one branch for spatial attention, one branch for channel attention, one branch for global feature representations and another branch for local feature representations. The attention branches focus on the relevant features of the image while suppressing the irrelevant backgrounds. The global and local branches intends to capture global context and fine-grained information, respectively. A set of ablation study shows that each component contributes to the increased performance of the LAGA-Net. Extensive evaluations on four popular body-based person Re-Id benchmarks and two publicly available hand datasets demonstrate that our proposed method consistently outperforms existing state-of-the-art methods. | |
| dc.funder | No external funder | |
| dc.identifier.citation | Baisa, N.L. (2024) Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images. Journal of Visual Communication and Image Representation, 103, 104207 | |
| dc.identifier.doi | https://doi.org/10.1016/j.jvcir.2024.104207 | |
| dc.identifier.uri | https://hdl.handle.net/2086/23989 | |
| dc.language.iso | en | |
| dc.peerreviewed | Yes | |
| dc.publisher | Elsevier | |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Person re-identification | |
| dc.subject | Deep representation learning | |
| dc.subject | Attention mechanisms | |
| dc.subject | Global features | |
| dc.subject | Part-level features | |
| dc.title | Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images | |
| dc.type | Article |