On the development of Robust Longitudinal Person Re-Identification

鲁棒纵向行人重识别的发展

• 批准号: 2822931
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2822931
• 关键词: development; Robust; Longitudinal; Person; Re

As one of the most rapidly emerging research areas, person re-identification (Re-ID) has been increasingly receiving attention in recent years. Based on the employed modality in question, the research on Re-ID could be broadly categorised into three branches: 1) retrieving a person of interest across multiple non-overlapping cameras, 2) re-identifying an individual based on a series of video clips, 3) establishing the longitudinally robust templates for biosignal-based person recognition.This project is devoted to thoroughly exploring the person Re-ID and further push the line within the selected research direction. With the advancement of deep neural networks and the increasing demand of intelligent video surveillance, the proposed question has gained significantly increased interest in the computer vision community in particular. Thanks to the availability of publicly databases, the successful candidate would potentially be trained to master both image and time-series data wrangling, which paves the way for the student with a much broader career perspective. One of the import papers related to this project is listed below [1]:[1] M. Ye, J. Shen, G. Lin, T. Xiang, L. Shao, and S. C. H. Hoi, "Deep Learning for Person Re-identification: A Survey and Outlook". IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.

作为最迅速新兴的研究领域之一，行人重新识别（Re-ID）近年来越来越受到关注。根据所采用的模式，Re-ID的研究可以大致分为三个分支：1）通过多个不重叠的摄像机检索感兴趣的人，2）根据一系列视频剪辑重新识别个人，3）建立基于生物信号的人识别的纵向鲁棒模板。该项目致力于彻底探索人的Re-ID并进一步推动所选研究的发展方向 方向。随着深度神经网络的进步和智能视频监控需求的不断增加，所提出的问题尤其在计算机视觉社区中引起了极大的兴趣。由于公共数据库的可用性，成功的候选人可能会接受培训来掌握图像和时间序列数据的处理，这为学生铺平了道路，拥有更广阔的职业前景。与该项目相关的一篇重要论文如下[1]：[1] M. Ye，J. Shen，G. Lin，T. Xian，L. Shao，and S. C. H. Hoi，“Deep Learning for Person Re-identification：A Survey and Outlook”。 IEEE 模式分析和机器智能汇刊，2021 年。