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Computer Science: Fully Funded EPSRC and Swansea University PhD Scholarship: On the development of Robust Longitudinal Person Re-Identification

   School of Mathematics and Computer Science

  Dr Su Yang  Friday, July 22, 2022  Funded PhD Project (Students Worldwide)

About the Project

Funding providers: Engineering and Physical Sciences Research Council (EPSRC) and Swansea University's Faculty of Science and Engineering

Subject areas: Computer Science, Pattern recognition, Machine Learning

Project start date: 

  • 1 October 2022 (Enrolment open from mid-September)

Project supervisors: Dr Su Yang and Professor Xianghua Xie

Aligned programme of study: PhD in Computer Science

Mode of study: Full-time

Project description: 

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.


Candidates must normally hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).

English Language requirements: If applicable – IELTS 6.5 overall (with at least 6.0 in each individual component) or Swansea recognised equivalent.

This scholarship is open to candidates of any nationality.

Funding Notes

This scholarship covers the full cost of tuition fees and an annual stipend of £16,062.
Additional research expenses will also be available.

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